Oscillatory neural associative memories with synapses based on memristor bridges

Abstract

An approach to the implementation of electronic associative memories with tunable weights based on the resistor bridges containing memristors—a bidirectional associative memory (BAM) and an associative memory based on the Hopfield network—is proposed. These memories we implement as a networks of coupled phase oscillators. The conditions for the use of the operational amplifier in a comparator mode for implementing the step activation function are determined. It is shown how to use the CMOS transistors switches to control the memristance value. The experiments using LTSPICE models show that for the reference binary images with size 3 × 3 the proposed networks converges to the reference images (and, accordingly, to their inversion) with a random uniform distribution of binary pixel values of the input images. In all experiments we have no error states in spite of the number of reference patterns exceeds the classical estimations for traditional BAM and Hopfield networks.