半导体学报2001，Vol.22Issue(5)：664-669,6.
采用遗传算法的一种可重构ANN的电路设计
Circuit Design of a Reconfigurable ANN with GA Training
摘要
Abstract
A novel sigmoid function generator is proposed.It is not only simple,fast,fit quite well with the ideal sigmoid function,but also programmable for the threshold and the gain factor.Thus,the neuron has wide application area and good prospect.Basic cells of the neural networks including the neuron,Gilbert multiplier,digital memory,D/A converter are designed.The benefit of Genetic Algorithm (GA) as an algorithm of the ANN is explained.A reconfigurable ANN composed of the above cells is designed,using GA as the training algorithm.The cells and the whole ANN are simulated with HSPICE,using level 47 transistor models for a standard 1.2μm CMOS process.Simulation results show that they all operate correctly and excellently.关键词
人工神经网络(ANN)/模拟集成电路/可重构/可编程分类
信息技术与安全科学引用本文复制引用
卢纯,石秉学..采用遗传算法的一种可重构ANN的电路设计[J].半导体学报,2001,22(5):664-669,6.
