Hybrid neural network for spatio-temporal pattern recognition

被引：0

作者：

Beijing Univ of Technology, Beijing, China ^{[1
]}

机构：

来源：

Zhongguo Shengwu Yixue Gongcheng Xuebao | / 2卷 / 1-6期

关键词：

Learning systems - Pattern recognition;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A hybrid neural network called TS-LM-SOFM was presented for detecting the spatio-temporal feature. Its top layer is a novel single layer temporal sequence recognizer called TS which can transform sparse temporal sequential pattern into abstract spatial feature representation, while its bottom layer is a modified self-recognizing feature map used as a spatial feature detector. A learning matrix connects the two layers. The experimental results showed that this network can well capture the spatio-temporal feature of input signal.

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