DISTRIBUTED CODING FOR DATA REPRESENTATION OF BACKPROPAGATION NEURAL-NETWORK CLASSIFIERS

被引：1
|
作者：
CHONG, CC
JIA, JC
机构：
[1] Nanyang Technological University, School of Electrical and Electronic Engineering
来源：
ELECTRONICS LETTERS | 1995年 / 31卷 / 21期
关键词：
BACKPROPAGATION; NEURAL NETS; PATTERN CLASSIFICATION;
D O I：
10.1049/el:19951244
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A new distributed input coding is derived by distributing the feature variables over a number of input nodes based on the distribution of the training data. Using this coding method representation, the range of each input node will be fully optimised; this enables the network to converge at a higher rate during training. The coding method also enables the network to maintain the generalisation capability of conventional normalisation coding.
引用
收藏
页码：1852 / 1854
页数：3
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