半导体学报2000，Vol.21Issue(12)：1164-1169,6.
Circuit Design of On-Chip BP Learning Neural Network with Programmable Neuron Characteristics
Circuit Design of On-Chip BP Learning Neural Network with Programmable Neuron Characteristics
摘要
Abstract
A circuit system of on chip BP(Back-Propagation) learning neural network with pro grammable neurons has been designed,which comprises a feedforward network,an error backpropagation network and a weight updating circuit. It has the merits of simplicity,programmability, speedness,low power-consumption and high density. A novel neuron circuit with pro grammable parameters has been proposed. It generates not only the sigmoidal function but also its derivative. HSPICE simulations are done to a neuron circuit with level 47 transistor models as a standard 1.2tμm CMOS process. The results show that both functions are matched with their respec ive ideal functions very well. The non-linear partition problem is used to verify the operation of the network. The simulation result shows the superior performance of this BP neural network with on-chip learning.关键词
hardware implementation of neural networks/CMOS analogue integrated circuits/programmabilityKey words
hardware implementation of neural networks/CMOS analogue integrated circuits/programmability分类
信息技术与安全科学引用本文复制引用
卢纯,石秉学,陈卢..Circuit Design of On-Chip BP Learning Neural Network with Programmable Neuron Characteristics[J].半导体学报,2000,21(12):1164-1169,6.基金项目
Project Supported by National Natural Science Foundation of China (Under Grant No. 69636030). （Under Grant No. 69636030）
