Memristor bridge synapse for better artificial neuron perceptron

Abstract

In artificial neural networks, the fourth passive element memristor can be utilized as an electronic synapse that serves as the interface between neurons. The artificial neuron composed of the memristor bridge synapse not only has the characteristics of low power consumption and high integration but also has a more simplified circuit and weight change conditions. Particularly, it has the ability of bionic intelligent information processing. This paper established two novel synaptic structures on the basis of memristor bridges (type 1 and type 2) and then synthetically analyzed how to realize the artificial neuron perceptron. Herein, the artificial synapses (type 1 and type 2) have the following characteristics: continuous changes in synaptic weights (positive, negative, and zero) and memory properties. Among them, the type 2 memristor bridge has the advantage of a wider range of weight updates for the synaptic circuit, which can realize the function of the artificial neuron perceptron with less error. This work lays the foundation for the future exploitation of artificial intelligence.