An effective associative memory for pattern recognition

被引：0
|
作者：
Kryzhanovsky, B
Litinskii, L
Fonarev, A
机构：
[1] Russian Acad Sci, Inst Opt Neural Technol, Moscow 119333, Russia
[2] Kean Univ, Dept Chem & Phys, Union, NJ 07083 USA
来源：
ADVANCES IN INTELLIGENT DATA ANALYSIS V | 2003年 / 2810卷
关键词：
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：
Neuron models of associative memory provide a new and prospective technology for reliable date storage and patterns recognition. However, even when the patterns are uncorrelated, the efficiency of most known models of associative memory is low. We developed a new version of associative memory with record characteristics of its storage capacity and noise immunity, which, in addition, is effective when recognizing correlated patterns.
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收藏
页码：179 / 186
页数：8
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