Sequential Memristor Crossbar for Neuromorphic Pattern Recognition

Abstract

Most of human's intelligent behaviors such as inference, prediction, anticipation, etc. are based on the processing of sequential data from human's sensory systems. Thus, a sequential memory that can process sequential information is very essential to mimic brain's intelligent behaviors. In this paper, we propose a new sequential memristor crossbar which is regarded as the first memristor circuit that copes with the sequential data. The new crossbar is composed of two layers which are the base layer and the sequential one, respectively. The base layer can recognize only static items one by one. The sequential layer can detect the serial order of items and find the best match with the detected sequence among many reference sequences stored in the memristor array. The new crossbar can recognize the tested sequences of items as well as 88.6% on average for the memristance variation of 0%. The variation tolerance is also tested from 0-% variation to 20-% variation in the proposed sequential crossbar.