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

页码：1852 / 1854

页数：3

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