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.

Design of Memristor Based Modified Synapse Circuit for Low-Power Neuromorphic Computing

“…The ndings of this thesis might be suitable for realizing the core of a spiking neural network architecture using two different types of memristor-based synapse circuitry improved by concentrating on state-of-the-art [10] and con guring a memristor to function as a synapse, enabling the STDP learning process aiming to achieve a low-power neuromorphic computing structure.…”

“…In this work, we have recon gured the synaptic circuits as our new ndings for a better arti cial neuron perceptron, the 2 memristor bridge synapse circuit (type 1, type 2) proposed by N. Wang et al, where they showed better symmetry of the synaptic weight with a wider range of weight updates [10]. We named two synaptic circuits two-resistor one capacitor (2R1C) and two-transistor one capacitor (2T1C)…”

“…However, the modi cation of those circuits from [10] is to improve the rate of ring at a certain threshold bias voltage with a wide range of characteristic gains.…”