基于忆阻器的量化特性可编程模数转换器OA

The analog-to-digital converter(ADC)serves as a key interface bridging the physical world and digital systems,playing a critical role in modern electrical systems such as edge sensing and intelligent computing.However,ADCs based on CMOS technology are constrained by manufacturing processes,which typically allow them to be constructed only using basic components such as capacitors,resistors,and transistors.The absence of non-volatile,tunable devices in the analog domain means that traditional ADCs often incur significant power consumption and chip area overhead when calibrating non-ideal characteristics or attempting to improve sampling efficiency across diverse scenarios.This paper introduces memristors into ADC design,leveraging their non-volatile and continuously tunable resistance to achieve in-situ calibration of circuit non-idealities and arbitrary programmability of quantization characteristics without any additional hardware overhead.Simulation results based on the 180 nm process demonstrate that the memristor-based ADC can perform in-situ circuit calibration solely through memristor programming,reducing the maximum differential nonlinearity by 71.6%and the maximum integral nonlinearity by 48.0%.Moreover,it maintains excellent calibration performance consistently across various process corners,temperatures,and supply voltages.Furthermore,by programming the memristors,arbitrary quantization curve shapes—such as linear,exponential,logarithmic,and"S"-shaped—can be reconfigured on the same ADC.This enables the memristor-based ADC to adapt its quantization curve to the statistical characteristics of different real-world signals(e.g.,images,audio),thereby maximizing sampling efficiency.Simulation results confirm that the memristor-based ADC achieves higher resolution with lower power consumption.The memristor ADC proposed in this paper highlights the significant potential of emerging memristor devices in advancing integrated circuit development for intelligent edge systems.