Memory-based convolutional neural network system

Abstract

A memory-based CNN, includes an input module, a convolution layer circuit module, a pooling layer circuit module, an activation function module, a fully connected layer circuit module, a softmax function module and an output module, convolution kernel values or synapse weights are stored in the NOR FLASH units; the input module converts an input signal into a voltage signal required by the convolutional neural network; the convolutional layer circuit module convolves the voltage signal corresponding to the input signal with the convolution kernel values, and transmits the result to the activation function module; the activation function module activates the signal; the pooling layer circuit module performs a pooling operation on the activated signal; the fully connected layer circuit module multiplies the pooled signal with the synapse weights to achieve classification; the softmax function module normalizes the classification result into probability values as an output of the entire network.