NEW ALGORITHMS FOR TRAINING FEEDFORWARD NEURAL NETWORKS

被引：20
|
作者：
KAK, S
机构：
[1] Department of Electrical and Computer Engineering, Louisiana State University, Baton Rouge
来源：
PATTERN RECOGNITION LETTERS | 1994年 / 15卷 / 03期
关键词：
FEEDFORWARD NEURAL NETWORKS; CORNER CLASSIFICATION; GENERALIZATION; MACHINE LEARNING;
D O I：
10.1016/0167-8655(94)90062-0
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new network that maps n-dimensional binary vectors into m-dimensional binary vectors using 3-layered feedforward neural networks is described. Algorithms to train this network are presented. The computing power of the new algorithms may be gauged from the example that the exclusive-Or problem that requires several thousand iterative steps using the backpropagation algorithm was solved in eight or fewer steps.
引用
收藏
页码：295 / 298
页数：4
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