The associative recall of spatial correlated patterns

被引:0
|
作者
Stanclova, Jana [1 ]
机构
[1] Charles Univ, Fac Math & Phys, Dept Software Engn, CR-11800 Prague 1, Czech Republic
来源
PROGRESS IN PATTERN RECOGNITON, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS | 2006年 / 4225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
The strategies for an associative recall can be based on associative memory models. However, the performance of standard associative memories is very sensitive to the number of stored patterns and their mutual correlations. With respect to huge amounts of spatial patterns (mostly correlated) to be processed, we have focused on an arbitrary number of associative memories grouped into several layers (Hierarchical Associative Memories - HAM). In the newly presented HAM2-model, the patterns are hierarchically grouped according to the "previous- I ayer" patterns. The HAM2-model uses the information recalled by the "previous-layer" to find an appropriate subset of "next-level" associative memories. To evaluate the performance of the HAM2-model, extensive simulations are carried out. The experimental results show the recall ability of the model in the area of associative pattern recall.
引用
收藏
页码:539 / 548
页数:10
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