Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: A CMOS hysteresis undervoltage lockout with current source inverter structure
An undervoltage lockout of hysteretic threshold of zero temperature coefficients
Low voltage adjustable CMOS Schmitt trigger
Low voltage low power current comparator circuit
Evolution of Low Drop Out Voltage Regulator in CMOS Technologies
Full On-Chip CMOS Low-Dropout Voltage Regulator
A Temperature and Process Compensated Ultralow-Voltage Rectifier in Standard Threshold CMOS for Energy-Harvesting Applications
A PROPOSED UNDER-VOLTAGE LOCKOUT OF COMPENSATED TEMPERATURE COEFFICIENT THRESHOLD VOLTAGE WITHOUT COMPARATOR
A mismatch-insensitive high-accuracy high-speed continuous-time current comparator in low voltage CMOS
Low-voltage, high-speed CMOS analog latched voltage comparator using the "flipped voltage follower" as input stage
Stabilizing the Frequency of Hysteretic Current-Mode DC/DC Converters
A CMOS Voltage Reference Based on Threshold Voltage for Ultra Low-Voltage and Ultra Low-Power
Design methodology using inversion coefficient for low-voltage low-power CMOS voltage reference
A CMOS low-dropout regulator with 3.3 μA quiescent current independent of off-chip capacitor
Design and comparison of CMOS Current Mode Logic latches
CMOS current comparator with Regenerative property
Nonlinear Control for DC–DC Converters Based on Hysteresis of the $C_{\rm OUT}$ Current With a Frequency Loop to Operate at Constant Frequency
Two New CMOS Schmitt Trigger Circuits based on Current Sink and Pseudo Logic Structures
Restoration of controllable hysteresis in partially depleted SOI CMOS Schmitt trigger circuits
CMOS Current-controlled Oscillators
Monolithic DC-DC boost converter with current-mode hysteretic control
CMOS analog circuit design via geometric programming
An argument for increasing TCP's initial congestion window
A customer value, satisfaction, and loyalty perspective of mobile application recommendations
Kafnets: kernel-based non-parametric activation functions for neural networks
Dropout training for SVMs with data augmentation