ESN neural network image classification processing method based on memristor

Abstract

The invention discloses an ESN neural network image classification processing method based on a memristor, and relates to the technical field of image processing. The unique memory characteristics andoperational capability of the memristor are utilized, an echo state network is given, an ESN neural network circuit based on the memristor is designed to meet the requirement for the storage capability in the image processing process, memory access operation of training data is reduced, and finally the purpose of improving the performance and efficiency of the overall neural network is achieved.According to the method, data storage and operation based on the memristor are fused; image data is used as a training object; an image preprocessing function is realized by utilizing convolution operation of the image. According to the method, basic logic operations required by image preprocessing are screened out, circuit design of the memristor is performed on the basic logic operations by referring to implicit circuits, so that a data storage and operation structure based on the memristor is completed, and memory access operation of training data is reduced by combining storage and operation of image data. The application of the invention can improve the performance of the whole neural network.

Description

Technical field [0001] The invention relates to an ESN neural network image processing method, and relates to the technical field of image processing. Background technique [0002] With the advent of the era of big data, neural networks have shown good effects in solving many practical problems, such as image recognition, speech recognition and some other time series predictions. However, as the scale of data to be processed increases and the complexity of types increases, the problem of neural network performance becomes more and more prominent, and more time-sensitive neural network technology needs to be studied. [0003] As a new type of electronic device, the memristor has a unique memory function and non-volatile storage capacity, and has huge application potential in artificial neural networks. It is precisely because of these characteristics that it is hopeful to solve a series of problems in hardware implementation of neural networks. However, since the memristor is stil...

AI Technical Summary

Problems solved by technology

[0034] In addition, due to the problem of the memristor process, although the memristor can theoretically realize multi-value storage, it is still not as stable as only digital logic 0 and 1 [34]

Images