A Self-Rectification and Quasi-Linear Analogue Memristor for Artificial Neural Networks

Abstract

A memristor with a bilayer electrolyte structure (Pt/C/NbOx/TiN) is proposed as a self-rectification and quasi-linear electronic synapse. The device shows self-rectifying analogue memristive behavior with > 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> rectification ratio, which can solve the sneak current problem in crossbar array without additional hardware burden. Under identical pulses in potentiation process, the device conductance is quasi-linearly changed with 9.16% nonlinearity. In addition, the conductance change rate of device is effectively tuned by altering amplitudes and frequencies of spike pulses. Benefiting from the quasi-linear conductance change characteristics, excellent classification accuracy (95.7%) is achieved for the application of handwritten digit classification with a two-layer perceptron based on MINST stimulation.