ENCODING METHOD FOR BIDIRECTIONAL ASSOCIATIVE MEMORY USING PROJECTION ON CONVEX-SETS

被引:23
|
作者
LEUNG, CS
机构
[1] Department of Computer Science, Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
来源
IEEE TRANSACTIONS ON NEURAL NETWORKS | 1993年 / 4卷 / 05期
关键词
D O I
10.1109/72.248465
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The traditional encoding method of bidirectional associative memory (BAM) suggested by Kosko is based on the correlation method with which the capacity is very small. The enhanced Householder encoding algorithm (EHCA) presented here is developed on the basis of the Householder encoding algorithm (HCA) and projection on convex sets (POCS). The capacity of BAM with HCA tends to the dimension of the pattern pairs. Unfortunately, in BAM with HCA there are two different interconnection matrices and hence BAM with HCA may not converge when the initial stimulus is not one of the library patterns. In EHCA the two matrices found by HCA are reduced into one matrix by POCS. Hence, the convergent property of BAM can be maintained. Simulation results show that the capacity of BAM with EHCA is greatly improved.
引用
收藏
页码:879 / 881
页数:3
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