An Aging Resilient Neural Network Architecture

Abstract

Recent artificial neural network architectures use memristors to store synaptic weights. The crossbar structure of memristors is used because of its dense structure and extreme parallelism. Transistor aging impacts their computational accuracy. An enhancement of the memristor-based neural network architecture is introduced using built-in current-based calibration circuit. It is shown experimentally that the proposed approach alleviates the cell aging effect.