Artificial neural networks: A tutorial

被引:2006
作者
Jain, AK
Mao, JC
Mohiuddin, KM
机构
[1] East China Normal University, Shanghai
[2] Docum. Image Anal. and Recog. Proj., Computer Science Department
[3] Department of Computer Science, Michigan State University, A417 Wells Hall, East Lansing
关键词
D O I
10.1109/2.485891
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Numerous advances have been made in developing intelligent programs, some inspired by biological neural networks. Researchers from many scientific disciplines are designing artificial neural networks (ANNs) to solve a variety of problems in pattern recognition, prediction, optimization, associative memory; and control. Although successful conventional applications can be found in certain well-constrained environments, none is flexible enough to perform well outside its domain. ANNs provide exciting alternatives, and many applications could benefit from using them. This article is for those readers with little or no knowledge of ANNs to help them understand the other articles in this issue of Computer. It discusses the motivation behind the development of ANNs; describes the basic biological neuron and the artificial computation model; outlines network architectures and learning processes; and presents multilayer feed-forward networks, Kohonen's self-organizing maps, Carpenter and Grossberg's Adaptive Resonance Theory models, and the Hopfield network. It concludes with character recognition, a successful ANN application.
引用
收藏
页码:31 / +
页数:1
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