计算机科学
炸薯条
CMOS芯片
反向传播
前馈
集合(抽象数据类型)
方案(数学)
人工神经网络
电子线路
生物神经网络
突触
芯片上的系统
计算机体系结构
拓扑(电路)
计算机硬件
人工智能
电子工程
嵌入式系统
工程类
电气工程
机器学习
神经科学
数学
电信
控制工程
数学分析
生物
程序设计语言
标识
DOI:10.1142/s0129065793000298
摘要
In this paper, an analogue, cascadable, CMOS chip set for artificial neural networks is presented. The chip set (a synapse chip and a neuron chip) offer on-chip back-propagation learning in a fully parallel, layered, feedforward network of arbitrary size and topology. The learning scheme is implemented with no extra circuits at the synapse sites (compared to the system without the learning scheme) and extra circuits of a complexity only about the same as the neurons at the neuron sites. Also, no additional wiring is required by the learning scheme. Measurements on an experimental chip set are presented.
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