计算机科学
人工神经网络
人工智能
前馈
机器学习
循环神经网络
前馈神经网络
人工神经网络的类型
理论计算机科学
控制工程
工程类
作者
Don Hush,Bill G. Horne
出处
期刊:IEEE Signal Processing Magazine
[Institute of Electrical and Electronics Engineers]
日期:1993-01-01
卷期号:10 (1): 8-39
被引量:1150
摘要
Theoretical results concerning the capabilities and limitations of various neural network models are summarized, and some of their extensions are discussed. The network models considered are divided into two basic categories: static networks and dynamic networks. Unlike static networks, dynamic networks have memory. They fall into three groups: networks with feedforward dynamics, networks with output feedback, and networks with state feedback, which are emphasized in this work. Most of the networks discussed are trained using supervised learning.< >
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