Title :
Encoding method for bidirectional associative memory using projection on convex sets
Author_Institution :
Dept. of Comput. Sci., Chinese Univ. of Hong Kong, Shatin, Hong Kong
fDate :
9/1/1993 12:00:00 AM
Abstract :
The traditional encoding method of bidirectional associative memory (BAM) suggested by Kosko (1988) 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
Keywords :
content-addressable storage; encoding; BAM; EHCA; HCA; bidirectional associative memory; convex sets; enhanced Householder encoding algorithm; projection; Associative memory; Computer science; Correlation; Costs; Encoding; Libraries; Magnesium compounds; Neurons; Steady-state;
Journal_Title :
Neural Networks, IEEE Transactions on