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### Dpcm And Delta Modulation

Signal to noise ratio (SNR). Delta Modulation The signal is first quantised into discrete levels, but the size of the step between adjacent samples is kept constant. What are the advantages of Delta Modulation? Overview Like PCM and DPCM, Delta Modulation (DM) is a form of digital signal encoding. This Second Edition contains additional material on the use of MATLAB functions in Simulink simulation, bandpass analog and complex digital modulation methods, time, frequency, code and orthogonal frequency division multiplexing, and direct sequence and frequency hopping spread spectrum. A transmitter radiates 9 kW without modulation and 10. Abstract: A study is presented on the digital coding of speech by means of a straightforward approximation of the time waveform. DPCM is listed in the World's largest and most authoritative dictionary database of abbreviations and acronyms Multilevel Delta Modulation with Switched First. Murat Torlak Delta Demodulator. Here, the difference between the signals is encoded based on its magnitude. Delta Modulation. Digital Communication: Pulse code modulation (PCM), differential pulse code modulation (DPCM), delta modulation (DM), Digital modulation and demodulation schemes: amplitude, phase and frequency keying schemes (ASK, PSK, FSK). Amplitude modulation, mathematical description and spectral characteristics of full carrier AM, DSBSC, SSB-SC, and VSB. delta modulation (DM): Analog-to-digital signal conversion in which (a) the analog signal is approximated with a series of segments, (b) each segment of the approximated signal is compared to the original analog wave to determine the increase or decrease in relative amplitude, (c) the decision process for establishing the state of successive bits is determined by this comparison, and (d) only. A digitally controlled companding scheme [8, 9] can be used to obtain a good telephone link with a bit. Design an optimal predictor for DPCM. speech coding include cellular communication, voice over internet protocol (VOIP), videoconferencing, electronic toys, archiving, and digital simultaneous voice and data (DSVD), as well as numerous PC-based games and multimedia applications. indx = dpcmenco(sig,codebook,partition,predictor) implements differential pulse code modulation to encode the vector sig. (MAY/JUN2006,8 MARKS) 19. Analyze 6. Another name for DM is pulse width modulation (PWM). Advantages of delta modulation: One of the major advantage of the delta modulation is consumption of low bandwidth. The higher frequencies have then been beaten down to lower frequencies… But there is a catch. Idle Channel Patterns in a DPCM Coder with a Fixed Quantizer-----56 9. The output signal (blue) is compared with the limits (green). Delta modulation (DM) is the simplest method for analog-to-digital conversion (ADC). Delta Modulation CODEC 2 MX629 CONTENTS , arks are held by their respective com panies. The layout of the paper is as follows. , special case of adaptive delta modulation), first proposed by Greefkes and Riemens in 1970. What is the highest modulation coefficient and percent modulation possible with a conventional AM system without causing excessive distortion? 11. Delta Modulation. 2 Differential Pulse-Code Modulation (DPCM), 307 6. 2 Adaptive delta modulation 6. According to the CCITT standard, if the PCM input bit flow is 64 kilobits per second (Kbps) (8 kHz sampling x 8-bit PCM. Delta modulation (DM or Δ-modulation)is an analog-to-digital and digital-to-analog signal conversion technique used for transmission of voice information where quality is not of primary importance. DPCM ; The PCM stands for pulse code modulation. Delta Modulation: Delta modulation, its draw backs, adaptive delta modulation, comparison of PCM and DM systems, Noise in PCM and DM systems. Sokullu */45 Processing Gain Output signal-to-noise – A free PowerPoint PPT presentation (displayed as a Flash slide show) on PowerShow. Another method of PCM that can be confused with Delta Modulation is the D(differential)PCM. t Companding with neat diagram Explain in detail (8) (8) (b) (a) Or (i) Write short n s on ISI and eye pattern (ii) Explain in detail about DPCM with neat diagram Explain in detail about CDMA and TDMA with neat diag Or (8) (8) (16) h co 15. -Vestigial-Sideband (VSB) Modulation -Phase-Locked Loop -Super-heterodyne Receiver 4. The parameters design of 1-bit adaptive delta modulations (ADM) systems with uniform sampling rate is well known. Pulse code modulation, DPCM and delta modulation. Murat Torlak Delta Demodulator. How does Pulse Code Modulation (PCM) differs from differential Pulse Code Modulation. 5 Laboratory Examples of Signal Quantization Using the TMS320C6713 DSK. DM coders are examples of a more general class of predic-tive coding systems called differential pulse code modulators (DPCM), which are based on exploiting intersample depen-. A band pass signal has a spectral range that extends from 20 to 82 KHz. Binary phase shift keying (BPSK). 2 Differential Pulse-Code Modulation (DPCM), 307 6. Table of contents for Modern digital and analog communication systems / B. The Delta Modulator comprises of a 1-bit quantizer and a delay circuit along with two summer circuits. What is differential pulse code modulation?19. Reviews "The biggest advantage of Modern Digital and Analog Communication is its accessible language and simple mathematical approaches that explain the difficult signal processing theories used in communication designs. Variations on PCM now include delta pulse-code modulation (DPCM) and adaptive delta pulse-code modulation (ADPCM). For each sample, the difference between the previous PCM code and the current code is expressed in terms of a fixed quantization value Ar (delta-r),. This reduces hardware complexity compared to a PCM or DPCM demodulator. Delta modulation is used when the source is highly correlated, for example speech coding with a high sampling rate. How does Pulse Code Modulation (PCM) differs from differential Pulse Code Modulation. Its main features are: The analog signal is approximated with a series of segments. The input signal is given by. Explain slope detector with neat diagram. Delta accentuation (DM or Δ-modulation)is an analog-to-digital and digital-to-analog arresting about-face address acclimated for manual of articulation advice area superior is not of primary importance. Delta Modulation –DM is single bit DPCM 10 Couch, Digital and Analog Communication Systems , Seventh Edition ©2007 Pearson Education, Inc. Explain frequency modulation with expression. Can produce 32767-bit (normal) and 93-bit (looped) sequences, selectable from the instrument's duty setting (V00 = normal, V01 = looped). Delta modulation (DM) is the simplest method for analog-to-digital conversion (ADC). List the drawbacks of pulse amplitude modulation. This in principle would require a sample-and-hold type circuit. { A real-time design for two advanced communications systems: the adaptive delta modulation \Simulation of DPCM and ADM Systems," 2012 UKSim. Prediction filtering and DPCM Delta Modulation ADPCM & ADM principles Linear Predictive Coding Properties of Line codes Power Spectral Density of Unipolar / Polar RZ & NRZ Bipolar NRZ Manchester. Adaptive differential pulse-code modulation (ADPCM) is a variant of differential pulse-code modulation (DPCM) that varies the size of the quantization step, to allow further reduction of the required data bandwidth for a given signal-to-noise ratio. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples is encoded into n-bit data. A device that converts an analog information signal to a pulse format. Section 2 describes the This paper discusses several Adaptive Delta Modulation basics of Delta Modulation technique. During coding, the present sample is compared with the previous and a 0 or 1 transmitted depending on whether the. Delta modulation (DM or Δ-modulation) is an analog-to-digital and digital-to-analog signal conversion technique used for transmission of voice information where quality is not of primary importance. Delta Modulation 13 Delta-Modulation - most popular alternative to PCM • analog signal is approximated by staircase function • only a single binary digit is required for each sample !!! • at each sampling time (kT), the function moves up or down a constant amount δ(step size) - the staircase function attempts to track the original. 1 Introducing the Software Application As previously stated, ADPCM is a complete digital transcoding process. There is no analog to digital converter required in delta modulation. 29-30 10 Frequency shift keying. Other Nyquist Filters Slide 57 Slide 58 Differential Pulse Code Modulation (DPCM) Slide 60 One Implementation of DPCM Slide 62 Delta Modulation (DM) DM Waveform Slide 65 Slide 66 Slide 67 ADM Block Diagram. First technique of image coding (~1952) 3. Define modulation coefficient and percent modulation. Chandra, NIT Durgapur – Walkie Talkie 10 CCA, NITD, 15th Feb, 2008 Electromagnetic waves are a form of radiated energy Wavelength ( λ) is the distance between a point on one wave and a similar point on the next wave (in meter). 2 Digital Audio Recording, 319. Home / Electronics Articles / Advantages, disadvantages and There are some disadvantages of PCM (pulse code modulation) which are given below, Difference between PCM and DPCM · Difference between pulse. Every time the output signal reaches one of the limits, the PWM signal… 📐 📓 📒 📝. 1BestCsharp blog 5,788,315 views. Explain the meaning of "Delta" in the definition of Delta Modulation. In other words: How do you map a delta value in the range [-65535, +65535] to an 8-bit code (and vice versa)? There are several different DPCM formats/implementations. (ADPCM) is a variant of differential pulse-code modulation (DPCM) that varies the. Its main features are: The analog signal is approximated with a series of segments. What are the limitation of Delta IEEE 1982 Hybrid Companding Delta Modulation with Variable. Compared to the existing DPCM based mobile fronthaul, significant EVM performance improvement is achieved using the same number of quantization bits. The Delta modulation is efficient when and only when signal is varying continuously with less variations. Bits/sample can be further reduced in DPCM. There are two drawbacks or errors in Delta Modulation , which are overcome by Adaptive Delta Modulation (ADM). Delta Modulation is a special case of DPCM. In delta modulation, a multi-bit. Stevens Institute of Technology Department of Electrical and Computer Engineering Course Outline EE465 Introduction to Communication Systems Text thS. It is a delta modulation with variable step size (i. Pulse code modulation (PCM), differential pulse code modulation (DPCM), delta modulation (DM), Digital modulation and demodulation schemes: amplitude, phase, and frequency keying schemes (ASK, PSK, FSK). figure 9 A - Delta Modulation. The efficiency and performance of these encoders can be improved. Real-Time Application of DPCM & ADM Systems. Every time the output signal reaches one of the limits, the PWM signal… 📐 📓 📒 📝. Adaptive differential pulse-code modulation (ADPCM) is a variant of differential pulse-code modulation (DPCM) that varies the size of the quantization step, to allow further reduction of the required data bandwidth for a given signal-to-noise ratio. There are two drawbacks or errors in Delta Modulation , which are overcome by Adaptive Delta Modulation (ADM). a) As one sample of x(kTs) is represented by only one bit after delta modulation, no elaborate word-level synchronization is necessary at the input of the demodulator. Delta modulation (DM or Δ-modulation)is an analog-to-digital and digital-to-analog signal conversion technique used for transmission of voice information where quality is not of primary importance. Differential pulse code modulation is a technique of analog to digital signal conversion. Explain uniform and non uniform quantisation (4 marks- APR/MAY2008) 21. We are offering delta, adaptive delta and delta sigma modulation, demodulation trainer - st2155. Subject Name: Analog and Digital Communication Year/Sem:II/III UNIT -I PART- A (2 MARKS) 1. Waveform quantization can also be classified as scalar or vector. Pulse code modulation is the procedure where each of the levels of an analog signal is assigned a value closest to a quantizer level used to quantize the signal. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples are encoded into n-bit data streams. Sigma Delta block diagram Below is the block diagram of a ﬁrst order Sigma Delta ADC stolen from the above named apps note. What is the advantage of delta modulation over pulse modulation s c h emes? Delta modulation encodes. PCM is the technique used for remodeling analog signal into digital signal. DM coders are examples of a more general class of predic-tive coding systems called differential pulse code modulators (DPCM), which are based on exploiting intersample depen-. EUdict (European dictionary) is a collection of online dictionaries for the languages spoken mostly in Europe. INSTITUTE OF AERONAUTICAL ENGINERING (Autonomous) UNIT-I Pulse Code Modulation S. Pulse code modulation is the procedure where each of the levels of an analog signal is assigned a value closest to a quantizer level used to quantize the signal. On the other hand, Differential PCM (DPCM), delta modulation (DM), and adaptive DPCM (ADPCM) have memory. Delta Modulation The simplest form of digitally coding an analog signal is with Delta Modulation. Differential Pulse Code Modulation (DPCM) Adaptive Differential PCM (ADPCM) Delta Modulation. Its main features are: The analog signal is approximated with a series of segments. As the sampling interval is reduced, the signal correlation will be higher. telephony the transportation rate should be kept every bit little as possible to salvage bandwidth because of economic ground. Set 1 - Digital Communication Test Questions. Delta modulation (DM or Δ-modulation)is an analog-to-digital and digital-to-analog signal conversion technique used for transmission of voice information where quality is not of primary importance. but in adaptive delta modulation, adaptive word is present. When the best 6fc predictor is used with an adaptive delta modulator (ADM) step size generator, the resulting pictures are similar in quality to 3fc predictors operating with a four-level adaptive DPCM quantizer. (h) State any TWO meaning of the term modulation as applied in data communication (ii)State any TWO advantages of Delta Modulation DM over Pulse Code Modulation PCM (iii)State any limitation of DM (5 Marks) SECTION B QUESTION 2 (a) Given data as 010011, sketch the encoded signals on the same plane of the following encoding schemes are used. Linear Delta-Modulation (LDM), Continuously Variable Slope Delta-Modulation (CVSD), and Adaptive Differential Pulse Code Modulation (ADPCM) are differential waveform coding techniques. Education News: IIT Delhi will hold the GATE 2020 Electronics and Communication Engineering examination in February at various centres across the country. Delta modulation The (non-adaptive) Delta modulation; Particular case of DPCM modulation; The signal quantization is performed on a single bit; It is necessary a strong correlation between the consecutive samples; The computation of the predicted signal is realized based on some. However, there are some limitations to Pulse Code Modulation and Delta Modulation that can cause data redundancy, quantization error, slope overload distortion and granular noise which result in a bad communication process. Below is the block representation of a delta modulator. So, to overcome the above-given problem the DPCM was devised. Here, the difference between the signals is encoded based on its magnitude. Drawbacks of delta modulation? this question is related to the analog to digital communication. Amplitude Shift Keying is one of the basic types of digital modulation techniques. For example, combining adaptive quantization with DPCM results in the commonly used coding algorithm, adaptive DPCM (ADPCM). 2 Differential Pulse-Code Modulation (DPCM), 307 6. In this paper efficient digital filter design techniques categorized as sigma-delta modulation based short word length (SWL) and multibit (or contemporary) techniques are reviewed in terms of hardware complexity, area, performance and power tradeoffs, synt. To get an idea on the improvement in performance that we can get from. There is noanalog to digital converter required in delta modulation. Moher, Communication Systems, 5 Edition, John Wiley & Sons, 2009. Digital Modulation systems, Modems, Introduction to teletraffic theory. modulation (DPCM) codec fòr TV signals by wav of DM/DPCM code conversion with digital filtering [10]. Contribution of course to meeting the requirements of ETAC/ABETCriterion 5:. Though pulse-code modulation is the the original process, it is still the method used to encode audio signals onto various forms of electronic media, such as compact disks (CDs), digital video disks (DVDs) and Blu-ray Discs™. In DPCM scheme if the base band signal is sampled at a rate much higher than the Nyquist rate purposely to increase the correlation between adjacent samples of the signal, so as to permit the use of a. codebook, a vector whose length exceeds the length of partition by one, prescribes a value for each partition in the quantization. When digital modulation techniques are used, speech signals must be coded into a format suitable for digital transmission. DPCM (Delta Pulse-code Modulation) is a conversion method traditionally used to transmit voice, often at the cost of quality to save on space or bandwidth. A delta modulation (DM or Δ-modulation) is an analog-to-digital and digital-to-analog signal conversion technique used for transmission of voice information where quality is not of primary importance. Definition of DPCM. PCM requires a very accurate clock. Delta Modulation 7. 9 Delta Modulation 6. PCM and DPCM assume that the source output is stationary. Digital Multiplexing. The input can be an analog signal or a digital signal. Draw the block diagram of DPCM. Signal to Noise Performance of Jayant's Exponentially Adaptive Delta Modulator — 64 12. An alternative, which overcomes some. Delta Modulation. 02 Unlike companded PCM, the αfor DPCM varies over a wide range, depending on the Properties of the input analog signal. DM is the simplest form of differential pulse-code modulation (DPCM) where t. Delta modulation (DM or ?-modulation) is an analog-to-digital and digital-to-analog signal conversion technique used for transmission of voice information where quality is not of primary importance. Explain slope detector with neat diagram. Prerequisite or corequisite: ECE 3410. However, there are some limitations to Pulse Code Modulation and Delta Modulation that can cause data redundancy, quantization error, slope overload distortion and granular noise which result in a bad communication process. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples is encoded into n-bit data. Resulting is the block diagram of a delta modulator. That reduces the amount of bits to be sent. Dialog Box. Definition: Differential Pulse Code Modulation (DPCM) is a modulation technique invented by the British Alec Reeves in 1937. 9 Delta Modulation 6. 4 Adriano Martins Moutinho Turma: 01 Pgina 2 de 10 Adriano. Delta modulation synonyms, Delta modulation pronunciation, Delta modulation translation, English dictionary definition of Delta modulation. If Predictor numerator has the form [0, x] and Predictor denominator is 1, then the modulation is called delta modulation. Pulse code modulation (PCM). Education News: IIT Delhi will hold the GATE 2020 Electronics and Communication Engineering examination in February at various centres across the country. 2 Differential Pulse-Code Modulation (DPCM), 307 6. This video will help you to understand the construction of DPCM, working of DPCM, use of DPCM. Time division multiplexing (TDM). Bit-Rate Delta modulation bit rate (r) = number ofbits transmitted/second. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples are encoded into n-bit data streams. The special case when m = 1 is called delta modulation. Prerequisite or corequisite: ECE 3410. The Communications Technologies Training System 4 includes the PAM/PWM/PPM applications, the PCM/ DPCM/Delta Modulation applications, the ASK/FSK/BPSK applications, and the QPSK/QAM/ADSL applications, as well as the corresponding courseware. DM: Delta Modulation. Digital Transmission of Analog Signals: PCM, DPCM and DM 6. According to the CCITT standard, if the PCM input bit flow is 64 kilobits per second (Kbps) (8 kHz sampling x 8-bit PCM. In delta modulation, amplitude of speech signal does not exceed maximum sinusoidal amplitude. The Opamp is tied in the inverting amplifier mode. ADPCM (Adaptive Differential Pulse Code Modulation) ADPCM is a type of DPCM (Differential Pulse Code Modulation), which sends (or store) the difference between consecutive samples instead of sending the entire magnitude of the sample. Modulation in which the peak-to-peak amplitude range of the signal to be transmitted is divided into a number of standard values, each having its own code; each sample of the signal is then transmitted as the code for the nearest standard amplitude. Waveform quantization can also be classified as scalar or vector. DPCM Terminology. Adaptive differential pulse code modulation (ADPCM) is a method used to convert analog signals to binary signals. Don't show me this again. Sokullu */45 Processing Gain Output signal-to-noise – A free PowerPoint PPT presentation (displayed as a Flash slide show) on PowerShow. PCM: The analog speech waveform is sampled and converted directly into a multibit digital code by an A/D. Delta Modulation (DM) Delta Modulation is a special case of DPCM. The technique converts the analog signals by taking frequent samples of the sound and representing the value of the sampled modulation in binary form. Performance Analysis and Optimal Filter Design for Sigma-Delta Modulation via Duality With DPCM true تحلیل عملکرد و طراحی صافی بهینه برای مدولاسیون سیگما - دلتا از طریق duality با dpcm. Presentation Summary : Audio Compression- DPCM Principles Differential pulse code modulation is a derivative of the standard PCM It uses an effect known as ‘frequency masking. Pulse code modulation and TDM. The predictor is a function that the DPCM encoder uses to produce the educated guess at each step. For 100% modulation what is the relationship between the voltage amplitudes of the side frequencies and the carrier? 12. An experiment with Differential Pulse Code Modulation that uses frequency modulation. It has a higher transmitter efficiency. Drawbacks of delta modulation? this question is related to the analog to digital communication. The PCM (pulse code modulation) can be use 4, 8 or 16 bit per sample. DPCM -- Effects of noise DPCM, like PCM, follows the 6-dB rule ⎟ = + α ⎠ ⎞ ⎜ ⎝ ⎛ n n S dB 6. Advantages of a Delta Modulator over DPCM. View Homework Help - DPCM-DM (1). Delta modulation requires a sampling rate much greater than the Nyquist rate (commonly four or five times the Nyquist rate). Define sampling and quantization?17. This is attained by using a feedback. Delta modulation is a form of DPCM which uses one bit per sample. Advantages of delta modulation: One of the major advantage of the delta modulation is consumption of low bandwidth. Delta Modulation is a shortened form of DPCM technique, also viewed as 1-bit DPCM scheme. Why Delta Modulation?Why Delta Modulation? • (DM or Δ-modulation) is an analog-to-digital conversion. Delta Modulation And Demodulation Computer Science Essay A modem to amelioscold despatch regularity execution that uses multiple harmonies concoct comprising harmonies technique and encoder combinations. However, a common problem with commonly used techniques, such as Pulse Coded Modulation (PCM) and Linear Delta Modulation (LDM), is that they negatively affect the communication process by causing quantization error, slope overload distortion, and granular noise. Definition: Differential Pulse Code Modulation (DPCM) is a modulation technique invented by the British Alec Reeves in 1937. Δ Modulation in Digital Switching ! An early application of delta modulation to voice encoding for digital electronic switching in telephony ! Motivation, for both switching and transmission, was to enable the per-. delta modulation (DM or Δ-modulation)is an analog-to-digital and digital-to-analog signal conversion technique used for transmission of voice information where quality is not of primary importance. Differential Pulse Code Modulation (DPCM) For the signals which does not change rapidly from one sample to next sample, the PCM scheme is not preferred. DPCM needs less number of quantization levels and hence less number of bits are needed to represent them. The noise generation in such systems cannot be denied [3]. Differential PCM systems find wide applications in speech and image compression. pulse code modulation (including DPCM), delta modulation, speech coding (vocoder), image/video cod-ing, and compression. The input can be an analog signal or a digital signal. All these are pulse digital modulation techniques. Radio wave propagation, effects of ionosphere and earth's curvature. Prerequisite or corequisite: ECE 3410. 7 Analysis-Synthesis Techniques 312 6. Sigma Delta block diagram Below is the block diagram of a ﬁrst order Sigma Delta ADC stolen from the above named apps note. Pulse-code modulation (PCM) Differential PCM (DPCM) Adaptive differential PCM (ADPCM) Delta modulation (DM) Adaptive delta modulation (ADM). Prediction filtering and DPCM - Delta Modulation - ADPCM & ADM principles-Linear Predictive Coding- Properties of Line codes- Power Spectral Density of Unipolar / Polar RZ & NRZ - Bipolar NRZ - Manchester. 8 Differential Pulse Code Modulation (DPCM) 6. Digital Communications I. Compare DPCM with PCM & DM systems (16) (i). Complexity PCM- System of pulse code modulation is quite complex DPCM- Differential pulse code modulation system is comparatively simple. 6) Attempt any TWO of the following. What is the abbreviation for Differential Pulse Code Modulation? What does DPCM stand for? DPCM abbreviation stands for Differential Pulse Code Modulation. Dyfed-Powys Police ‘Community Messaging’ (DPCM) is now available force-wide. Delta modulation seeks to overcome the problem of high bandwidth requirement in conventional PCM. 2 Adaptive delta modulation 6. Double-Loop Sigma-Delta Modulation with dc Input, by Ning He, Federico Kuhlmann, and Andres Buzo; IEEE Transactions on Communications, vol. Delta Modulation & Demodulation: What is Delta Modulation? A message signal m(t) has a BW of 1KHz and exhibits a maximum rate of change of change of 2 Volts/sec the signal is sampled at a sampling frequency of 20 KHz and Quantized using a delta modulator the minimum step size to avoid slope overload is———- …. The slope of the analog signal is greater than the delta modulator can maintain and is called slope overload. Explain noise present in delta modulation in details. On the other hand, communication engineers have developed two additional digital communication systems which are the Adaptive Delta Modulation (ADM) and the Differential Pulse Coded Modulation (DPCM) in order to solve the aforementioned problems. Microprocessor & VLSI Design Lab. The Communications Technologies Training System 4 includes the PAM/PWM/PPM applications, the PCM/ DPCM/Delta Modulation applications, the ASK/FSK/BPSK applications, and the QPSK/QAM/ADSL applications, as well as the corresponding courseware. com - id: 4b7152-MmVlN. 1 Digital Audio in Telephone Transmission Systems, 317 6. DCPM is a system which enables us to issue fast time messages to you and, enables you to play a part in policing. If the redundancy is reduced, then the overall bitrate will decrease and the number of bits required to transmit one sample will also reduce. In PCM, each sample is quantized to one of 2R amplitude level,. And then it is possible, in effect, to delta-modulate each of these channels separately. Below is the block representation of a delta modulator. We calculate the granular quantizing noise for a delta modulator that has unequal positive and negative step sizes. When digital modulation techniques are used, speech signals must be coded into a format suitable for digital transmission. Explain slope detector with neat diagram. Delta Modulator. The library is said to be an axle in any Educational Institute, where all other activities rotate around it. In delta modulation, a multi-bit. Delta Modulation The signal is first quantised into discrete levels, but the size of the step between adjacent samples is kept constant. Delta Modulation CODEC 2 MX629 CONTENTS , arks are held by their respective com panies. The most common predictive quantization method is differential pulse code modulation (DPCM). 92 Appendix A6. The special case when m = 1 is called delta modulation. Name of the Lab: Microprocessor & VLSI Design Lab Brief Introduction: The Microprocessor Laboratory contains facilities that inculcate the knowledge of programming skills by executing various programs like arithmetic operations, code conversions, searching and sorting algorithms covered in the Microprocessor course. Modulation in which the peak-to-peak amplitude range of the signal to be transmitted is divided into a number of standard values, each having its own code; each sample of the signal is then transmitted as the code for the nearest standard amplitude. The closed loop voltage gain of the Opamp is given by. How to reduce the quantization noise that occurs in DM? 12. A bipolar D/A converter is used for playback to convert the successive difference values to an analog waveform. DM can be considered as a 1-bit differential PCM (DPCM) system. telephony the transportation rate should be kept every bit little as possible to salvage bandwidth because of economic ground. Compare AM & FM (6 Marks) 3. These comprise the tools required for the study of communication systems. SAMPLING AND PULSE CODE MODULATION 251 294 and the Rate Of 14 71 6 8 12 13 16 6. Keuntungan yang diperoleh adalah bahwa jumlah bit yang diperlukan untuk proses penyandian menjadi lebih sedikit. Frank Prediction Coding Techniques Audio PCM: Pulse Code Modulation (digitizing algorithm using logarithmic coding) DPCM: Differential PCM ADPCM: Adaptive DPCM DM: Delta Modulation Video MC: Motion Compensation DPCM Compute a predicted value for next sample, store the difference between prediction and actual value. Delta modulation The (non-adaptive) Delta modulation; Particular case of DPCM modulation; The signal quantization is performed on a single bit; It is necessary a strong correlation between the consecutive samples; The computation of the predicted signal is realized based on some fixed methods independent of the variation law of the previous. Stevens Institute of Technology Department of Electrical and Computer Engineering Course Outline EE465 Introduction to Communication Systems Text thS. HOW to generate PPM signal from P WM signal? Explain with proper. 97 References 6. PCM and DPCM assume that the source output is stationary. , $\tilde{x}[0]=0$), and that the quantization step $\Delta=1$ for. Module 4 [08] Introduction to coding theory:. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples are encoded into n-bit data. Download Presentation Delta Modulation An Image/Link below is provided (as is) to download presentation. DPCM is listed in the World's largest and most authoritative dictionary database of abbreviations and acronyms Multilevel Delta Modulation with Switched First. (5 points) Briefly describe the similarities and differences between Differential Pulse Code Mod. Differential Pulse Code Modulation (DPCM) (Continued) The advantage of DPCM is the reduced amount of information that must be transmitted if we maintain the same SNR or an improved SNR if we maintain the same amount of information. 1 Introduction Quite a few of the information bearing signals, such as speech, music, video, etc. DPCM for which a single bit is used in the quantization table becomes delta modulation (DM). See first of all we need to know what is a differential pulse code modulation (DPCM). (EC322: Introduction to communication systems). Data supply with LEDs E. IT & Software Differential Pulse Code Modulation (DPCM) - Quantization and Coding Summary and Exercise are very important for perfect preparation. The PCM (pulse code modulation) can be use 4, 8 or 16 bit per sample. 1: PSD of a waveform process with discrete amplitudes 6. Signal to Noise Performance of Jayant's Exponentially Adaptive Delta Modulator — 64 12. In other words, the relevance of this work relies on its ability. modulation (PCM) linear and non-linear, delta modulation (DM) and demodulation, adaptive delta modulation (ADM). but in adaptive delta modulation, adaptive word is present. DPCM- In this case, feedback exists 6. The term ﬁrst order just means that you can cascade these things to get better performance, just like you can cascade ampliﬁers to get more gain. We had already discussed about ASK modulation circuit before. Explain phase discrimination detector with neat. 40-42 14 Delta modulation. Draw DPCM transmitter and receiver and explain role of predictor 18. Introduction Sigma-Delta modulation (Σ-ΔM or Δ-ΣM) is a technique for converting analog signals into digital data. Bit-Rate Delta modulation bit rate (r) = number ofbits transmitted/second. The maximum frequency of the signal is 5 KHz. Prediction filtering and DPCM - Delta Modulation - ADPCM & ADM principles-Linear Predictive Coding- Properties of Line codes- Power Spectral Density of Unipolar / Polar RZ & NRZ - Bipolar NRZ - Manchester. For this purpose Delta Modulation, adaptative Delta transition, Differential Pulse-Code transition is used to compact the information. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples are encoded into n-bit data streams. DPCM stands for Delta Pulse Code Modulation. In PCM, each sample is quantized to one of 2R amplitude level,. Amplitude modulation (AM), frequency modulation (FM), quantization, and pulse code modulation (PCM). An adaptive multi-bit delta and sigma-delta modulation and demodulation technique, wherein a one-bit modulator generates a binary output signal from an analog input signal and a multi-bit adapter for generating a scaling signal for scaling a step-size of the sigma-delta modulator. Digital Modulation TechniquesIntroduction ASK, FSK, PSK, DPSK, DEPSK, QPSK, M-ary, PSK, ASK, FSK, similarity of BFSK and BPSK. 2 Receiver Model and Figure of Merit: Linear Modulation 7. Report Abuse. Delta Modulation –DM is single bit DPCM 10 Couch, Digital and Analog Communication Systems , Seventh Edition ©2007 Pearson Education, Inc. partition is a vector whose entries give the endpoints of the partition intervals. Mention the applications of DM. The transmitter and receiver implementation is very much simple for delta modulation. Zxx DPCM delta counter, changes the delta counter directly, affects volume of noise and triangle. Pulse Code Modulation and Time Division Multiplexing. Some pulse modulation schemes also allow the narrowband analog signal to be transferred as a digital signal (i. Delta Modulator. ADPCM (Adaptive Differential Pulse Code Modulation) ADPCM is a type of DPCM (Differential Pulse Code Modulation), which sends (or store) the difference between consecutive samples instead of sending the entire magnitude of the sample. Differential PCM (DPCM), Delta Modulation (DM) and Adaptive Delta Modulation (ADM), comparison. In scalar. The technique is a variation of the digitized method known as pulse code modulation. HOW to generate PPM signal from P WM signal? Explain with proper. DM is the simplest form of differential pulse-code modulation (DPCM) where the difference between successive samples are encoded into n-bit data streams. Pulse code modulation (PCM), differential pulse code modulation (DPCM), delta modulation (DM), Digital modulation and demodulation schemes: amplitude, phase, and frequency keying schemes (ASK, PSK, FSK). GATE Multiple Choice Questions, GATE Guide, and the GATE Cloud series.


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Math Help - Center of Mass

1. Center of Mass

I have two problems here that i cant figure out

EDIT find the center of mass given that the mass is constant

1.)the "triangular" region in the first quadrant between the circle x^2+y^2=9 and the lines x=3 and y =3 (Hint: use geomentry to find the area).

2.) Find the center of mass of a thin plate covering the region between the x-axis and the curve y= 2/x^2. 1<=x<=2 if the plates density ate the point (x,y)
is delta(x)=x^2

2. (1)You can view the the region as subtracting the rectangle from the quater-circle.

Now the centroid of the rectangle is trivial (1.5,1.5) und the area is 9.

The centroid of a quater-circle is located on the line $y=x$ (that is symettry) and is $\frac{4r}{3\pi}$ (a known formula). In this case $r=3$. Thus the centroid is $\frac{4(3)}{3 \pi}=\frac{4}{\pi}=1.27$. Thus, $(x,y)=(1.27,1.27)$. And has area $\frac{1}{4}\pi (3)^2=7.06$.

Thus, by the composite centroid formula we have,
$\bar x= \frac{(1.5)(9)-(1.27)(7.06)}{9+7.06}$

$\bar y=\frac{(1.5)(9)-(1.27)(7.06)}{9+7.06}$

3. hmmm.... my book say's i should get 2/(4-pie).... i think ur #### gives me the c of m of the semicircle... i want to find the c of m of the triangular shape made by the semicircle and x=3 and y=3

format: plain


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# Chapter 1 - Tools of Geometry - 1-5 Exploring Angle Pairs - Practice and Problem-Solving Exercises - Page 39: 37

a) x=19.5 b) $m\angle RQS=43$, $m\angle TQS=137$ c) $m\angle RQS+m\angle TQS\overset?=180$ $43+137\overset?=180$ $180=180\checkmark$

#### Work Step by Step

Use the definition of a linear pair: $m\angle RQS+m\angle TQS=180$ $(2x+4)+(6x+20)=180$ $8x+24=180$ $8x+24-24=180-24$ $8x=156$ $8x\div8=156\div8$ $x=19.5$ Substitute to find the measures: $m\angle RQS=2x+4+2(19.5)+4=39+4=43$ $m\angle TQS=6x+20=6(19.5)+20=117+20=137$ To check your answer, verify the sum of the angles is 180.

After you claim an answer you’ll have 24 hours to send in a draft. An editor will review the submission and either publish your submission or provide feedback.


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## Archive for April, 2007

### What’s In a (University) Name?

| Peter Klein |

An organization’s name is an important part of its identity. Names can also be valuable signals to market participants about mission, values, and strategy. Certainly, names seem to matter: a 2001 paper by Michael J. Cooper, Orlin Dimitrov, and Raghavendra Rau, “A Rose.com by Any Other Name,” documented a positive and significant stock-price reaction to announcements of adding “dot-com” to company names. (No word on the reaction to the reverse, as when Monster.com changed its name to Monster in 2003.)

Two universities in my state have gotten into the act. In 2005 Southwest Missouri State University changed its name to Missouri State University to reflect a more national orientation. (In most US states the “University of XYZ” is the original state university and “XYZ State University” is the newer, land-grant institution; in Missouri, however, the land-grant designation was given in 1870 to the already-existing University of Missouri, officials of which strongly opposed giving the name Missouri State to a rival institution.) Now the University of Missouri system has announced that the University of Missouri-Rolla, one of four campuses in the state system (and home of guest blogger Chihmao Hsieh), will change its name to Missouri University of Science and Technology. The name change is “is part of chancellor John S. Carney III’s goal of making UMR one of the nations top 5 technological research universities by 2010,” according to a news release. But will it smell as sweet?

Update: My old college classmate Jim  Surowiecki, author of The Wisdom of Crowds, wrote about corporate name changes for Slate back in 1997.

| Peter Klein |

Good tips from Jonathan Shewchuk (via Craig Newmark). Written for computer scientists but mostly applies across the board. Highlights:

A talk of 30 minutes or less should be an advertisement for the paper, not a replacement.

It is disturbing that so many presentations have large wasted bands of space on the border of every slide, as if to taunt the audience — “I could have used a readable font, but it’s just you.”

You communicate most powerfully when your every movement, facial expression, and utterance is in the service of the words you are saying right now, and no unproductive movement takes place.

Good speaking is about rhythm. The most common type of bad speaker delivers one talk-length paragraph at a uniform speed, never slowing for emphasis.

Most everything else, especially aesthetics, is learned through practice and feedback.

Includes great cartoons, like the one above.

### The Dark Side of Capital Pooling

| Peter Klein |

The great advantage of joint-stock companies, whether public or private, is the ability to create value by pooling capital. Unfortunately, capital pools can also be channeled to activities that destroy value. (HT: Against Monopoly.)

### Teaching Management through Demotivators

| Peter Klein |

Like many of you, I’ve considered using teaching my managerial economics course using a Dilbert collection as a secondary, or even primary, text. There are so many good ones! One could also use the wickedly funny Demotivators to illustrate key managerial and organizational theories and concepts. For example:

### How Well Do You Know Your Advisor?

| Chihmao Hsieh |

Unless you’ve already seen it, here’s a quite popular comic strip glorifying and lampooning school, and particularly graduate studies. Below was the comic for 04/23 (infinitely clearer version here). Another recent good one is the sheet used for Seminar Bingo. (Caution: The comic’s archive is a happily illuminating time sink.)

### The Language of Economists (and Sociologists)

| Peter Klein |

From the “news that will shock no one” department come the results of this linguistic analysis of four economics journals, the American Economic Review, Economic Journal, Journal of Economic Perspectives, and American Journal of Economics and Sociology, along with a control group containing the American Journal of Sociology, Journal of Microscopy, and Journal of the American Mathematical Society:

The present study aims to add to our knowledge about economic rhetoric by conducting a data-driven analysis of economic academic discourse, both synchronically in its contemporary form, and diachronically over the past four decades. We find (1) that linguistically, economics is clearly an academic genre of its own, (2) that there are at the same time clear differences in vocabulary and style usage across economic journals, and (3) that there have been major developments in economic prose during the past four decades. We argue that there is some, albeit tentative, evidence that the discipline may face an increasing methodological gap.

Here is the paper, “What Do Economists Talk About? A Linguistic Analysis of Published Writing in Economic Journals” by Nils Goldschmidt and Benedikt Szmrecsanyi (American Journal of Economics and Sociology 66, no. 2, April 2007). The “gap” is between journals like the AER and EJ that use increasingly formal, empirical (scientistic?) terminology and journals like JEP and AJES that favor broader, social-science terms and concepts (“justice,” “society,” “culture,” “institutions”). Interestingly, use of social-science terminology in the AER, relative to the other journals, dropped between 1965 and 1980 but rose again between 1980 and 1990. Too early to reflect the Freakonomics phenomenon, to be sure, but perhaps a marker for economic imperialism more generally?

### Political Instability and Financial Development

| Peter Klein |

The latest salvo in the debate over the role of legal origin in financial-market performance comes from Mark Roe. In “Political Instability and Financial Development” (with Jordan Siegel) he argues that political instability is a more important determinant of financial development than trade openness, latitude, and, particularly, legal origin as modeled by LLSV. “Surprisingly, despite the widespread view in the law and finance literature of legal origin’s importance, not only is political stability highly robust to legal origin, but, for many years, our results for key indicators and specifications neither show Common Law to be consistently superior nor French Civil Law to be consistently inferior to other legal families in generating strong financial development outcomes.”

See also my “Politics and Productivity” on the interaction between political institutions, economic freedom, and national economic performance.

### The Market for Organization Equals USD 7.6B

| Chihmao Hsieh |

Home organization (in 2009), that is.

A CNN article posted online last month has re-appeared in the headlines today, probably in response to the woman who is virtually selling virtually (sic) all her belongings in one single auction on EBay (see the actual listing here). To spare you the reading, the article essentially describes our “hyper-consumptive society deluged by its own belongings,” mentions the TV shows and firms that create products and promote services to help us organize our belongings, and highlights associations like the new-but-fast-growing National Association of Professional Organizers.

Personally, in the last few years I’ve become much more mindful of the number of discrete items I keep at home, that mindfulness mainly a side effect of thinking in terms of this kind of complexity theory and this subfield of cognitive science.

### Five Blogs That Make Me Think

| Peter Klein |

When Nicolai and I started this blog a year ago we were hoping for a plural readership. Now that we’ve hit that target we can move on to the next: making our readers think. Fortunately, we’ve already succeeded with at least one reader: Nijma of Camel’s Nose, who named O&M one of five blogs that make her think. This is one of those “memes” in which each blogger named is supposed to name five bloggers who make him think, who in turn name five bloggers that make them think, and so on, until everyone is nested under someone else, sort of like Amway but without money changing hands.

The Thinking Blog’s Ilker Yoldas is responsible for all this (and for supplying the nice graphic above). Yoldas describes the exercise as a humanistic alternative to blog ranking systems like Technorati based on quantitative analysis of linking patterns, just as “human-powered” search engines like ChaCha are alternatives to Google.

Anyway, I’ll play along. Here are five blogs that make me think. (To make things interesting I’ve excluded the sites listed already on the blogroll below.)

| Peter Klein |

Next Tuesday, May 1, is the deadline for submitting an abstract to the University of Missouri’s Frameworks for Entrepreneurship Research conference. Keynote speakers include O&M favorites Pierre Desrochers and Randy Westgren (who comments as REW) so you don’t want to miss it.

### Puzzles and Problems Redux

| Peter Klein |

In an earlier post, “Economics: Puzzles or Problems?”, I noted the tendency of talented young economists to focus on clever, yet ultimately unimportant, puzzles rather than the traditional “big problems” of economics (inflation, unemployment, poverty, economic growth, regulation, political economy, etc.). Steve Levitt, and the brand of “Freakonomics” he inspired, is usually singled out as the main culprit here. A recent piece in The New Republic, “Freaks and Geeks,” takes Levitt and company to task not only for wasting their time and talent, but also for being dilettantes who get key facts wrong (a point raised by Steve Sailer). Here are responses from Levitt (very unhappy), Joshua Angrist (also unhappy, though not for personal reasons), Josh Wright (mildly unhappy), and Greg Mankiw (neutral). Sadly, no one has picked up my (very clever) reference to the relationship between Wittgenstein and Popper.

| Peter Klein |

I’m pleased to announce that Fabio Chaddad of IBMEC is joining the Division of Applied Social Sciences at the University of Missouri. Fabio’s research deals with networks, supply-chain management, cooperatives, corporate finance, and other aspects of strategy and organization. He may even be worthy of a guest-blogger spot at O&M!

### Happy Birthday to Us

| Peter Klein |

April 25, 2007 marks the one-year anniversary of Organizations and Markets. Thanks to our readers and to guest bloggers Joe Mahoney, Dick Langlois, Lasse Lien, David Gordon, Cliff Grammich, Steve Postrel, and Chihmao Hsieh for making the past year so much fun and challenging. We look forward — if Nicolai will forgive the pomo phrase — to “continuing the conversation.”

### Does Hayek Still Matter?

| Nicolai Foss |

I may be wrong, but I have the feeling that the thought of Friedrich von Hayek is receiving less and less attention. This worries me for personal reasons — I wrote my Master’s Thesis in economics in 1989 on Hayek’s business cycle theory, and his work has continuously served as an important source of inspiration to me (e.g., this paper) as well as to countless others — and for the reason that Hayek’s thought is too important to vanish in influence. (more…)

### Frank Knight and the Chicago School

| Peter Klein |

Frank Knight is generally regarded, along with Jacob Viner, as the founder of the Chicago school of economics. But Knight’s relationship to the later Chicago school of Friedman, Stigler, and Director is ambiguous. Knight’s theories of capital and competition were incorporated into the mainstream Chicago (and contemporary neoclassical) tradition but his account of profit and entrepreneurship, his quasi-Austrian methodology (inherited from his teacher Herbert J. Davenport), and his eclectic social and political theories were largely ignored or forgotten.

Ross Emmett has a new paper, “Did the Chicago School Reject Frank Knight? Assessing Frank Knight’s Place in the Chicago Economics Tradition,” exploring this in detail. The conclusion: “Without [Knight’s] initiation of eaching price theory and persistence in defending it, there ould be no Chicago tradition. Yet the methodological approach and research infrastructure which propelled the Chicago School to a central position in the economics profession owe little or nothing to him.”

(Incidentally, critics of economics often target a stylized version of Chicago economics circa 1970 (see here), but these critics often seem unaware that the Chicago school of economics no longer exists. While there is still a (top-notch) economics department at the University of Chicago, there is no longer a distinct Chicago approach. The economics taught at Chicago is the same as the economics taught at MIT, Harvard, Stanford, or any other top mainstream department.)

### How is What is an Opportunity a Valuable Research Question?

| Chihmao Hsieh |

In introducing the April 2007 Special Issue of Small Business Economics, guest editors Jeffery McMullen and Lawrence Plummer, and Zoltan Acs ask “What is an Entrepreneurial Opportunity?” First, the abstract:

The nature and source of entrepreneurial opportunity are important issues for understanding how markets function and come into being. In addition to describing the forum held on the topic and summarizing the contributions of the articles that appear in the special issue, this article shares a number of lessons learned during the workshop and the editorial process. We explore three of the most important reasons for confusion about the opportunity construct: (1) the “objectivity” of opportunity, (2) the perceived importance of one particular individual in determining the direction of the social world and (3) what distinguishes the sub-class of “entrepreneurial” opportunity from the broader category of opportunity in general. Finally, we offer some directions for future research by illuminating important issues that emerged from the workshop but that remain largely unanswered by the papers of this special issue.

Needless to say, the authors courageously untangle some fundamental concepts (i.e. different types of ‘objectivity’ as it might relate to the notion of opportunity). Yet a sentence in the article’s second paragraph gave me pause: “…without a clear understanding of the nature of opportunity, formulating logically consistent prescriptions for both policy and practice is problematic because any theoretical basis of empirical results would be incomplete” (p. 273). (more…)

### The Growth of Cities: A Formal Model

| Peter Klein |

Luís Bettencourt, José Lobo, Dirk Helbing, Christian Kühnert, and Geoffrey West’s paper “Growth, Innovation, Scaling, and the Pace of Life in Cities” (Proceedings of the National Academy of Sciences 104, no. 17, April 24, 2007) is getting a lot of attention, garnering plugs in Scientific American and Nature. They use data on innovation, employment, wages, GDP, consumption, crime, disease, housing, and infrastructure from US, European, and Chinese cities to estimate a “power law scaling function” linking demographic, socioeconomic, and behavioral indicators to city size. Such indicators, $Y(t),$ are related to population $N(t)$ according to

$Y(t)=Y_0N(t)^{\beta}.$

Findings:

Many diverse properties of cities from patent production and personal income to electrical cable length are shown to be power law functions of population size with scaling exponents, $\beta,$ that fall into distinct universality classes. Quantities reflecting wealth creation and innovation have $\beta \approx 1.2 >1$ (increasing returns), whereas those accounting for infrastructure display $\beta \approx 0.8<1$ (economies of scale). We predict that the pace of social life in the city increases with population size, in quantitative agreement with data, and we discuss how cities are similar to, and differ from, biological organisms, for which $\beta<1.$ Finally, we explore possible consequences of these scaling relations by deriving growth equations, which quantify the dramatic difference between growth fueled by innovation versus that driven by economies of scale. This difference suggests that, as population grows, major innovation cycles must be generated at a continually accelerating rate to sustain growth and avoid stagnation or collapse.

For more on cities see these posts on Jane Jacobs and this one on clusters. Here is Ed Glaeser’s influential 1992 paper (with Hedi Kallal, Jose Scheinkman, and Andrei Shleifer) on growth in cities. Other important Glaeser papers on cities include this one with Jesse Shapiro, this one with Albert Saiz, and this one with Christopher Berry. Here is Glaeser’s review of Richard Florida’s Creative Class and here is Florida’s blog. And here is an interesting special issue of the Review of Austrian Economics on the new urbanism.

Update: Here is Florida’s take on the paper.

### Contronymns

| Peter Klein |

Re Chihmao’s post: English also has quite a few contronyms, words that are their own antonyms. Here is a list, including these that appear often in business administration and social-science research:

• custom — usual, special
• discursive — proceeding coherently from topic to topic, moving aimlessly from topic to topic
• enjoin — prescribe, prohibit
• first degree — most severe (e.g., murder), least severe (e.g., burn)
• mean — average, excellent (e.g., “plays a mean game”)
• oversight — error, care
• rent — buy use of, sell use of
• transparent — invisible, obvious

HT: LRC.

### Theoretical vs. Teórico vs. 理论: How the Precision of Foreign Language Relates to the Cost of Innovation

| Chihmao Hsieh |

Recently, bloggers Nicolai and Peter have highlighted the unfortunate confusions corresponding to the usage of the terms conceptual vs. theoretical, as well as usage of “method” vs. “methodology.”

A few inquiries could deserve some attention. First, is this confusion specific to those terms as they appear in the English language? For instance, perhaps other languages have their own labels indicating the concepts of “conceptual” and “theoretical” but the root words (e.g. concept, theory) involved are less substitutable. I’m also guessing that other languages have distinct labels for “method” and “methodology,” whereby less confusion emerges. (more…)

### Media, Dummy Variables, Fame, Fathers of Sociology, and School Shootings

| Chihmao Hsieh |

By now, all readers of this blog are probably well-aware of the massacre at Virginia Tech that took 33 lives. (My own prayers go out to all those affected by the tragedy.)

Some controversies are bound to be re-visited during and after the investigation (e.g. gun control) but others are starting to reveal themselves as mainstream for the first time. Namely, the media itself may be promoting these types of shootings. (more…)

## Authors

Nicolai J. Foss | home | posts
Peter G. Klein | home | posts
Richard Langlois | home | posts
Lasse B. Lien | home | posts

## Guests

Former Guests | posts

## Our Recent Books

Nicolai J. Foss and Peter G. Klein, Organizing Entrepreneurial Judgment: A New Approach to the Firm (Cambridge University Press, 2012).
Peter G. Klein and Micheal E. Sykuta, eds., The Elgar Companion to Transaction Cost Economics (Edward Elgar, 2010).
Peter G. Klein, The Capitalist and the Entrepreneur: Essays on Organizations and Markets (Mises Institute, 2010).
Richard N. Langlois, The Dynamics of Industrial Capitalism: Schumpeter, Chandler, and the New Economy (Routledge, 2007).
Nicolai J. Foss, Strategy, Economic Organization, and the Knowledge Economy: The Coordination of Firms and Resources (Oxford University Press, 2005).
Raghu Garud, Arun Kumaraswamy, and Richard N. Langlois, eds., Managing in the Modular Age: Architectures, Networks and Organizations (Blackwell, 2003).
Nicolai J. Foss and Peter G. Klein, eds., Entrepreneurship and the Firm: Austrian Perspectives on Economic Organization (Elgar, 2002).
Nicolai J. Foss and Volker Mahnke, eds., Competence, Governance, and Entrepreneurship: Advances in Economic Strategy Research (Oxford, 2000).
Nicolai J. Foss and Paul L. Robertson, eds., Resources, Technology, and Strategy: Explorations in the Resource-based Perspective (Routledge, 2000).


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# Time-reversal transformation for two-component bosonic models

Consider a two-component bosonic model $\mathcal{H}=-t\sum_{i\sigma}{b_{i\sigma}b_{i+1\sigma}^\dagger}+h.c. +\sum_{i\sigma\sigma^\prime}U_{\sigma\sigma^\prime}n_{i\sigma}n_{i\sigma^\prime}$. Here $\sigma,\sigma^\prime$ aretwo the pseudo spin, they can take $\uparrow,\downarrow$. I want to know how to define the time-reversal transformation for such two-component bosonic models. Is the definition same as fermion models?

• It is probably not the same as for fermion models (where time reversal flips the spin) – why should time reversal change the kind of boson (though if the kinds of bosons are some effective particles like right movers and left movers it probably will). I guess the correct time reversal will be independent time reversal for both boson components (but I can be wrong). – Sebastian Riese Aug 26 '15 at 20:56
• An answer can be found at physicsoverflow.org/33696 – Arnold Neumaier Oct 20 '15 at 11:16


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# statsmodels.tsa.regime_switching.markov_regression.MarkovRegression.fit¶

MarkovRegression.fit(start_params=None, transformed=True, cov_type='approx', cov_kwds=None, method='bfgs', maxiter=100, full_output=1, disp=0, callback=None, return_params=False, em_iter=5, search_reps=0, search_iter=5, search_scale=1.0, **kwargs)

Fits the model by maximum likelihood via Hamilton filter.

Parameters
start_paramsarray_like, optional

Initial guess of the solution for the loglikelihood maximization. If None, the default is given by Model.start_params.

transformedbool, optional

Whether or not start_params is already transformed. Default is True.

cov_typestr, optional

The type of covariance matrix estimator to use. Can be one of ‘approx’, ‘opg’, ‘robust’, or ‘none’. Default is ‘approx’.

cov_kwdsdict or None, optional

Keywords for alternative covariance estimators

methodstr, optional

The method determines which solver from scipy.optimize is used, and it can be chosen from among the following strings:

• ‘newton’ for Newton-Raphson, ‘nm’ for Nelder-Mead

• ‘bfgs’ for Broyden-Fletcher-Goldfarb-Shanno (BFGS)

• ‘lbfgs’ for limited-memory BFGS with optional box constraints

• ‘powell’ for modified Powell’s method

• ‘basinhopping’ for global basin-hopping solver

The explicit arguments in fit are passed to the solver, with the exception of the basin-hopping solver. Each solver has several optional arguments that are not the same across solvers. See the notes section below (or scipy.optimize) for the available arguments and for the list of explicit arguments that the basin-hopping solver supports.

maxiterint, optional

The maximum number of iterations to perform.

full_outputbool, optional

Set to True to have all available output in the Results object’s mle_retvals attribute. The output is dependent on the solver. See LikelihoodModelResults notes section for more information.

dispbool, optional

Set to True to print convergence messages.

callbackcallable callback(xk), optional

Called after each iteration, as callback(xk), where xk is the current parameter vector.

return_paramsbool, optional

Whether or not to return only the array of maximizing parameters. Default is False.

em_iterint, optional

Number of initial EM iteration steps used to improve starting parameters.

search_repsint, optional

Number of randomly drawn search parameters that are drawn around start_params to try and improve starting parameters. Default is 0.

search_iterint, optional

Number of initial EM iteration steps used to improve each of the search parameter repetitions.

search_scalefloat or array, optional.

Scale of variates for random start parameter search.

**kwargs

Additional keyword arguments to pass to the optimizer.

Returns
MarkovSwitchingResults


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# Open SourceMolecular Dynamics

### Sidebar

#### For Developers

exercises:2015_uzh_molsim:h2o_diff

# Diffusion constant, viscosity and size effects

When simulating liquids or solids under periodic boundary conditions, we are making two fundamental approximations:

1. We simulate an infinite system, thus neglecting the fact that any real-world system is finite. This approximation becomes problematic, when the real-world system to be studied consists only of a few simulation cells.
2. We impose the condition that the properties of the system under study repeat exactly from one simulation cell to the next. The quality of this approximation depends on the system under study and the quantity of interest.

Here, we want to calculate the diffusion constant of water at room temperature ($T=300\,\text{K}$). Since we are interested in a property of bulk water, we don't need to worry about the first approximation. But we need to pay attention to the second one. The theory derived in 10.1021/jp0477147 allows us to estimate the finite size effects in the diffusion constant $D_{pbc}(L)$, calculated under periodic boundary conditions with cell size $L$. With this information at hand, we will be able to extrapolate the results for finite cell sizes to the diffusion constant $D=\lim\limits_{L\rightarrow \infty}D_{pbc}(L)$, effectively getting rid of the second approximation.

Calculating transport properties typically requires lots of sampling. Start the MD simulation for 32 water molecules and see how far you can get (aim at least for 200 ps).

This simulation will take a considerable amount of time. Tasks 1 and 2 can already be completed, while it is running.
1. While the job is running, check the output of CP2K to verify that all is fine. What is the average temperature?
2. We want to simulate diffusion at room temperature. Why aren't we using the $NVT$ ensemble? Hint: Think about how thermostats work.
3. Use the provided script ./get_t_sigma file.ener to calculate the standard deviation of the temperature for your simulation as well as for the provided simulations of larger cells containing 64, 128 and 256 water molecules.
4. How are temperature fluctuations expected to depend on system size? Use gnuplot's fitting functionality to check whether they follow the corresponding law. Hint: See e.g. "Understanding Molecular Simulations" by Frenkel and Smit, sections 4.1 and 6.2. (2P)

The mean squared displacement (msd) is defined as $$\text{msd}(t) = \langle |r(t+t_0)-r(t_0)|^2 \rangle$$ where the average $\langle \ldots \rangle$ runs over all particles in the system.

Our simulations are not large enough to obtain reasonable statistics just from averaging over all water molecules. We therefore perform an additional average over the time $t_0$: $\text{msd}(t)$ is calculated as an average over all non-overlapping time windows of width $t$ that fit into the total simulation time $T$. We have provided a Fortran program that uses this algorithm to extract the msd from a trajectory in a .xyz file.

gfortran msd.f90 -o msd.x  # compile msd.x executable
./msd.x < msd.in           # check input file 'msd.in' before you run!

Per default, msd.x writes the msd in units of $\unicode{x212B}^2$ as a function of time in fs.

Once you have calculated the msd, have a look into section III of the article on how to fit the diffusion constant.

1. We have precalculated trajectories for 64, 128 and 256 water molecules (ask your teaching assistant). Use msd.x to calculate the msd, modifying msd.in as needed. Note: msd.x may run up to 30 minutes for the largest cell.
2. Plot the msd as a function of time on a double logarithmic scale. Can you identify different regimes? Why does the signal become noisy towards long times? (2P)
3. Obtain the diffusion constant $D_{pbc}$ by fitting a line through the mean square displacement data in the range $2-10$ ps.
4. Compare against the values in Table I of the article. Note: We are using a slightly different force field, but the values should be of a similar magnitude. If not, check your units!

When your MD of the 32 water molecules has finished (for example on the next day), you can start fitting the diffusion constant.

1. Calculate $D_{PBC}(L)$ also for the 32 water molecules.
2. Plot $D_{PBC}$ as a function of $1/L$, where $L$ is the length of the edge of the simulation box.
3. Perform a linear fit of this curve to obtain the diffusion constant $D=D_{pbc}(L=\infty)$
4. Use equation (12) in the article to calculate the viscosity $\eta$ from the slope of $D_{PBC}(1/L)$.


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### Seminar talk at the BGU OA Seminar

This coming Thursday (July 2nd, 14:10 Israel Time) I will be giving a talk at the Ben-Gurion University Math Department’s Operator Algebras Seminar. If you are interested in a link to the Zoom please send me an email.

I will be talking mostly about these two papers of mine with co-authors: older one, newer one. Here is the title and abstract:

Title: Matrix ranges, fields, dilations and representations

Abstract: In my talk I will present several results whose unifying theme is a matrix-valued analogue of the numerical range, called the matrix range of an operator tuple. After explaining what is the matrix range and what it is good for, I will report on recent work in which we prove that there is a certain “universal” matrix range, to which the matrix ranges of a sequence of large random matrices tends to, almost surely. The key novel technical aspects of this work are the (levelwise) continuity of the matrix range of a continuous field of operators, and a certain quantitative matrix valued Hahn-Banach type separation theorem. In the last part of the talk I will explain how the (uniform) distance between matrix ranges can be interpreted equivalently as a “dilation distance”, which can be interpreted as a kind of “representation distance”. These vague ideas will be illustrated with an application: the construction of a norm continuous family of representations of the noncommutative tori (recovering a result of Haagerup-Rordam in the d=2 case and of Li Gao in the d>2 case).

Based on joint works with Malte Gerhold, Satish Pandey and Baruch Solel.

### A review of my book A First Course in Functional Analysis

A review for my book A First Course in Functional Analysis appeared in Zentralblatt Math – here is a link to the review. I am quite thankful that someone has read my book and bothered to write a review, and that zBMath publishes reviews. That’s all great. Now I have a few words to say about it. This is an opportunity for me to bring up the subject of my book and highlight some things worth highlighting.

I am not too happy about this review. It is not that it is a negative review – actually it has a rather kind air to it. However, I am somewhat disappointed in the information that the review contains, and I am not sure that it does the reader some service which the potential readers could not achieve by simply reading the table of contents and the preface to the book (it is easy to look inside the book in the Amazon page; of course, it is also easy to find a copy of the book online).

The reviewer correctly notices that one key feature of the book is the treatment of $L^2[a,b]$ as a completion of $C([a,b])$, and that this is used for applications in analysis. However, I would love it if a reviewer would point out to the fact that, although the idea of thinking about $L^2[a,b]$ as a completion space is not new, few (if any) have attempted to actually walk the extra mile and work with $L^2$ in this way (i.e., without requiring measure theory) all the way up to rigorous and significant applications in analysis. Moreover, it would be nice if my attempt was compared to other such attempts (if they exist), and I would like to hear opinions about whether my take is successful.

I am grateful that the reviewer reports on the extensive exercises (this is indeed, in my opinion, one of the pluses of new books in general and my book in particular), but there are a couple of other innovations that are certainly worth remarking on, and I hope that the next reviewer does not miss them. For example, is it a good idea to include a chapter on Hilbert function spaces in an introductory text to FA? (a colleague of mine told me that he would keep that out). Another example: I think that my chapter on applications of compact operators is quite special. This chapter has two halves: one on integral equations and one on functional equations. Now, the subject of integral equations is well trodden and takes a central place in some introductions to FA, and one might wonder whether anything new can be done here in terms of the organization and presentation of the material. So, I think it is worth remarking about whether or not my exposition has anything to add. The half on applications of compact operators to functional equations contains some beautiful and highly non-trivial material that has never appeared in a book before, not to mention that functional equations of any kind are rarely considered in introductions to FA; this may also be worth a comment.


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## Ephemeris quality during the Galileo outage

I have spoken about the Galileo incident that occurred in July in several posts already: here I took a look at the navigation message during the outage, here I used MGEX navigation RINEX files to look at the navigation message as the system was recovering, and here I did the same kind of study for the days preceding the outage. Other people, such as the NavSAS group from Politecnico di Torino, and Octavian Andrei from the Finnish Geospatial Research Institute, have made similar studies by looking at the $$\mathrm{IOD}_{\mathrm{nav}}$$, data validity and health bits of the navigation message.

However, I haven’t seen any study about the quality of the ephemerides that were broadcast on the days surrounding the outage. The driving force of the studies has been whether the ephemerides were being updated or not, without taking care to check if the ephemerides that were broadcast were any good at all.

The NavSAS group commented seeing position errors of several hundreds of metres during the outage when using the broadcast ephemerides. That is to be expected, as the ephemerides were already many hours old (and indeed many receivers refused to use them, considering them expired). Here I will look at whether the ephemerides were valid (i.e., described the satellite orbit and clock accurately) in their time interval of applicability.

This post is an in-depth look written for a reader with a good GNSS background.

Continue reading “Ephemeris quality during the Galileo outage”

## Measuring the ED4YAE 10GHz beacon

Last week, the 10GHz beacon ED4YAE on Alto del León was installed again after having been off the air for quite some time (I think a couple of years). The beacon uses a 10MHz OCXO and a 500mW power amplifier, and transmits CW on 10368.862MHz. The message transmitted by the beacon is DE ED4YAE ED4YAE ED4YAE IN70WR30HX, followed by a 5.8 second long tone.

On 2019-08-31, I went to the countryside just outside my city, Tres Cantos, to receive the beacon and do some measurements. The measurements were done around 10:00 UTC from locator IN80DO68TW. The receiving equipment was a 60cm offset dish from diesl.es, an Avenger Ku band LNB, and a LimeSDR USB. Everything was locked to a 10MHz GPSDO. The dish was placed on a camera tripod at a height of approximately 1.5 metres above the ground.

In this post I show the results of my measurements.

Continue reading “Measuring the ED4YAE 10GHz beacon”

## Galileo outage revisited

A few weeks ago, a presentation by Octavian Andrei, of the Finnish Geospatial Research Institute, appeared in YouTube showing technical details about the Galileo constellation outage that happened between July 12 and 16. In the presentation, Octavian studies the navigation data gathered by a geodetic receiver in Metsähovi, showing anomalies in some of the parameters of the navigation message, such as the $$\text{IOD}_{\text{nav}}$$, the SISA (signal in space accuracy) and the DVS (data validity status).

Back in July, I looked at the navigation data from the outage in this post, where I used navigation RINEX files collected by the IGS MGEX to study changes and anomalies in the navigation message. In that post I concentrated on July 16 and 17, to show what happened as the system was coming back online. Octavian has discovered some very interesting anomalies that happened before the incident, on July 10 and 11. Indeed, the first anomaly happened at 13:40 GST on July 10, well before July 11 21:50 GST, when the navigation message stopped being updated.

Thus, in view of Octavian’s discoveries, I have revisited my study, including also data from July 10 and 11, and paying special attention to the $$\text{IOD}_{\text{nav}}$$ parameter, which can be seen to have the most interesting behaviour in Octavian’s presentation.

## Measuring the gain of a dish

Here I want to show a technique for measuring the gain of a dish that I first learned from an article by Christian Monstein about the Moon’s temperature at a wavelength of 2.77cm. The technique only uses power measurements from an observation of a radio source, at different angles from the boresight. Ideally, the radio source should be strong and point-like. It is also important that the angles at which the power measurements are made are known with good accuracy. This can be achieved either with a good rotator or by letting an astronomical object drift by on a dish that is left stationary.

Continue reading “Measuring the gain of a dish”

## Trying to find the DSLWP-B crash site

As you may well know, DSLWP-B, the Chinese lunar orbiting Amateur satellite crashed with the Moon on July 31 as a way to end its mission without leaving debris in orbit. I made a post with my prediction, which showed the impact point southeast of Mare Moscoviense, in the far side of the Moon. Phil Stooke was more precise and located the impact point near the Van Gent crater.

Our plan is to get in contact with the LRO team and try to find the crash site in future LRO images. We are confident that this can be done, since they were able to locate the Beresheet impact site a few months ago. However, to help in the search we need to compute the location of the impact point as accurately as possible, and also come up with some estimate of the error to define a search area where we are likely to find the crash. This post is a detailed account of my calculations.

Continue reading “Trying to find the DSLWP-B crash site”

## Precise orbit determination for Lucky-7

In one of my previous posts, I used measurements from the GPS receiver on-board the Lucky-7 cubesat in order to find the TLE that best matched its orbit, and help determine which NORAD ID corresponded to Lucky-7.

Now I have used the same GPS measurements to perform precise orbit determination with GMAT. Here I describe the results of this experiment.

Continue reading “Precise orbit determination for Lucky-7”

## More DSLWP-B lunar surface images identified

In my last posts about DSLWP-B, I have been showing all the images of the lunar surface that were taken by the satellite during the last weeks of the mission, and tried to identify to which area of the Moon each image corresponded. For several of them, I was able to give a good identification using Google Moon, but for many of the latest images I was unable to find an identification, since they show few or none characteristic craters.

Thus, for these images I only gave a rough prediction of which area of the Moon was imaged by using GMAT and the published ephemeris from dslwp_dev. This doesn’t take into account camera pointing, orbit or shutter time errors.

Phil Stooke has become interested in this and he has managed to identify many of the images, even some containing very little detail, which I find impressive. No wonder, Phil is the author of several atlases of space exploration of the Moon and Mars, so he knows a lot of lunar geography.

Phil tells me that he has used Quickmap, which is a very nice tool that I didn’t know of. It is much more powerful than Google Moon. He recommends to switch to an equidistant cylindrical projection and set as a basemap layer the “WAC mosaic (no shadows) map”, which contains images with the sun directly overhead. This resembles the images taken by DSLWP-B better, since these are always taken with the sun at a high elevation, because the camera always points away from the sun. It is interesting to see how the appearance of the surface changes between the “no shadows” and “big shadows” maps.

In this post I show the locations of the images identified by Phil.

Continue reading “More DSLWP-B lunar surface images identified”

## Lucky-7 TLE matching using GPS data

SkyFox Labs is having some trouble identifying the TLE corresponding to their Lucky-7 cubesat. The satellite was launched on July 5 in launch 2019-038 and a good match among the TLEs assigned to that launch has not being found yet. Over on Twitter, Cees Bassa has analyzed some SatNOGS observations and he says that NORAD ID 44406 seems the best match. However, this TLE has already been identified by Spire as belonging to one of their LEMUR satellites.

Fortunately, Lucky-7 has an on-board GPS receiver, and the team has been collecting position data recently. This data can be used to match a TLE to the orbit of the satellite, and indeed is much more accurate than the Doppler curve, which is the usual method for TLE identification.

Jaroslav Laifr, from the Lucky-7 team, has sent me the data they have collected, so that I can study it to find a matching TLE. The study is pretty simple to do with Skyfield. I have obtained the most recent TLEs for launch 2019-038 from Space-Track and computed the RMS error between each of the TLEs and the GPS measurements. The results can be seen in this Jupyter notebook.

The best match is NORAD ID 44406, with an RMS error of 8.7km. The second best match is NORAD ID 44404 (which is what SatNOGS has been using to track Lucky-7), with an RMS error of 51.3km. Most other objects have an error larger than 100km.

Therefore, my conclusion is clear. It is very likely that Spire misidentified NORAD ID 44406 as belonging to LEMUR 2 DUSTINTHEWIND early after the launch, when the different objects hadn’t drifted apart much. NORAD ID 44406 is a good match for Lucky-7. It will be interesting to see what Spire says in view of this data.

## Second Moon observation with my QO-100 station.

In May 25, the Moon passed through the beam of my QO-100 groundstation and I took the opportunity to measure the Moon noise and receive the Moonbounce 10GHz beacon DL0SHF. A few days ago, in July 22, the Moon passed again through the beam of the dish. This is interesting because, in contrast to the opportunity in May, where the Moon only got within 0.5º of the dish pointing, in July 22 the Moon passed almost through the nominal dish pointing. Also, incidentally this occasion has almost coincided with the 50th anniversary of the arrival to the Moon of Apollo 11, and all the activities organized worldwide to celebrate this event.

The figure below shows the noise measurement at 10366.5GHz with 1MHz and a 1.2m offset dish, compared with the angular separation between the Moon and the nominal pointing of the dish (defined as the direction from my station to Es’hail 2). The same recording settings as in the first observation were used here.

The first thing to note is that I made a mistake when programming the recording. I intended to make a 30 minute recording centred at the moment of closest approach, but instead I programmed the recording to start at the moment of closest approach. The LimeSDR used to make the recording was started to stream one hour before the recording, in order to achieve a stable temperature (this was one lesson I learned from my first observation).

The second comment is that the maximum noise doesn’t coincide with the moment when the Moon is closest to the nominal pointing. Luckily, this makes all the noise hump fit into the recording interval, but it means that my dish pointing is off. Indeed, the maximum happens when the Moon is 1.5º away from the nominal pointing, so my dish pointing error is at least 1.5º. I will try adjust the dish soon by peaking on the QO-100 beacon signal.

The noise hump is approximately 0.085dB, which is much better than the 0.05dB hump that I obtained in the first observation. It may not seem like much, but assuming the same noise in both observations, this is a difference of 2.32dB in the signal. This difference can be explained by the dish pointing error.

The recording I have made also covers the 10GHz Amateur EME band, but I have not been able to detect the signal of the DL0SHF beacon. Perhaps it was not transmitting when the recording was made. I have also arrived to the conclusion that the recording for my first observation had severe sample loss, as it was made on a mechanical hard drive. This explains the odd timing I detected in the DL0SHF signal.

The next observation is planned for October 11, but before this there is the Sun outage season between September 6 and 11, in which the Sun passes through the beam of the dish, so that Sun noise measurements can be performed.

## DSLWP-B activities for the third week of July

During this week, the Amateur payload of DSLWP-B was active during the following slots:

• 14 Jul 19:00 to 21:00
• 15 Jul 12:00 to 14:00
• 17 Jul 04:40 to 06:50
• 18 Jul 20:50 to 22:50
• 20 Jul 14:20 to 16:20
• 21 Jul 05:30 to 07:30

Among these, the Moon was visible from Europe only on July 14, 18 and 21, so Dwingeloo only observed these days, which were mainly devoted to the download of SSDV images of the lunar surface. As usual, the payload took an image automatically at the start of each slot, so some of the slots were used for autonomous lunar imaging, even though no tracking was made from Dwingeloo.

This post is a detailed account of the activities done with DSLWP-B during the third week of July.

Continue reading “DSLWP-B activities for the third week of July”