TY - JOUR
T1 - Encoding Method for Bidirectional Associative Memory Using Projection on Convex Sets
AU - Leung, C. S.
PY - 1993/9
Y1 - 1993/9
N2 - 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. © 1993 IEEE
AB - 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. © 1993 IEEE
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U2 - 10.1109/72.248465
DO - 10.1109/72.248465
M3 - RGC 22 - Publication in policy or professional journal
SN - 1045-9227
VL - 4
SP - 879
EP - 881
JO - IEEE Transactions on Neural Networks
JF - IEEE Transactions on Neural Networks
IS - 5
ER -