现代电子技术Issue(18)：41-43,47,4.
一种基于ART2神经网络的算法改进
An improved algorithm based on ART2 neural network
摘要
Abstract
Aiming at the problems of setting vigilance parameter and pattern drift produced in the process of classification identification of the traditional ART2 neural network,a new ART2 neural network model based on modified algorithm is presen-ted in this article to solve problems concerning analysis of pattern identification. Reasonable vigilance parameter needed by clus-tering is deduced through the processing of self-organization,weighting and iteration. In order to conduct reasonable classifica-tion of clustering objects,the measures of slowing learning rate which can be realized by modifying the weight training of ART2 neural network to reduce the speed of pattern drifting should be taken. The experimental results have proved that the new model is of high validity and feasibility.关键词
ATR2神经网络/警戒值/模式漂移/模式识别Key words
ATR2 neural network/security value/pattern drift/pattern recognition分类
信息技术与安全科学引用本文复制引用
胡鑫,叶青,郭庚山..一种基于ART2神经网络的算法改进[J].现代电子技术,2014,(18):41-43,47,4.
