A memristor-based perceptron neural network circuit and an adjusting method thereof

Abstract

The invention discloses a memristor-based perceptron neural network circuit and an adjusting method thereof. The circuit comprises a memristor module, a weight conversion module, a net input module and a mapping function module, wherein the memristor module is connected with the weight conversion module, the weight conversion module is connected with the net input module, and the net input moduleis connected with the mapping function module. According to the method, firstly, an image of a resistance value and time relation of the memristor is adjusted to be approximate to a straight line, andthen an image of a weight value and time relation is adjusted to be approximate to a straight line. The memristor resistance value which is linearly changed can more accurately replace the synaptic weight value of the neural network, and the trained synaptic weight value of the neural network is stored by utilizing the resistance value of the memristor, so that the conversion between the memristor resistance value and the neuron synaptic weight value is realized, and the problem that a traditional neuron circuit cannot accurately adjust the synaptic weight value is solved.

Description

technical field [0001] The invention belongs to the field of realization of perceptron neural network circuits, and in particular relates to a memristor-based perceptron neural network circuit and an adjustment method thereof. Background technique [0002] The artificial neural network is to imitate it on the basis of human's understanding of the brain's neural network, so that an intelligent network system that can have certain functions can be artificially constructed. The perceptron is the basis of the artificial neural network, so the perceptron neural network circuit is of great significance. [0003] Neural networks can be implemented by software and hardware. When the tasks processed by artificial neural networks do not need to run very fast, most designers of neural networks use software applications on computers or workstations to implement neural networks instead of seeking special additional hardware to implement them, but even Even the fastest serial processor ...

AI Technical Summary

Problems solved by technology

[0005] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a memristor-based perceptron neural network circuit to solve the problem that the traditional neuron circuit cannot accurately adjust the synapse weights

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