Associative memory with a sparse encoding mechanism for storing correlated patterns

✍ Scribed by Makoto Hirahara; Natsuki Oka; Toshiki Kindo

• Publisher: Elsevier Science
• Year: 1997
• Tongue: English
• Weight: 864 KB
• Volume: 10
• Category: Article
• ISSN: 0893-6080
• DOI: 10.1016/s0893-6080(97)00038-5

✦ Synopsis

Gu(freund (Neural networks with hierarchically correlated patterns. Physical Review A, 37, 570-577, 1988

) has proposed a model for storing hierarchically correlated patterns where ancestor patterns are correlated with descendant ones. However, there is a problem of small storage capacity. Furthermore, we must give ancestors in the learning phase, and determine the value of the parameter on which the capacity and the basins of attraction strongly depend. To overcome these problems, we present a model (CASM) consisting of the first associative memory to form ancestors from their descendants and the second associative memory to store sparse difference patterns which have only information on differences between the formed ancestors and the descendants. To evaluate the performance of CASM, extensive simulations are carried out. The results show that the capacity increases with increasing correlation between the ancestors and the descendants, and is as large as that of sparsely encoded associative memory. The basins of attraction become larger with decreasing correlation, and do not depend on loading level.