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Bidirectional associative memories

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1 Author(s)
B. Kosko ; Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA

Stability and encoding properties of two-layer nonlinear feedback neural networks are examined. Bidirectionality is introduced in neural nets to produce two-way associative search for stored associations. The bidirectional associative memory (BAM) is the minimal two-layer nonlinear feedback network. The author proves that every n-by- p matrix M is a bidirectionally stable heteroassociative content-addressable memory for both binary/bipolar and continuous neurons. When the BAM neutrons are activated, the network quickly evolves to a stable state of two-pattern reverberation, or resonance. The stable reverberation corresponds to a system energy local minimum. Heteroassociative information is encoded in a BAM by summing correlation matrices. The BAM storage capacity for reliable recall is roughly m<min (n,p). It is also shown that it is better on average to use bipolar {-1,1} coding than binary {0.1} coding of heteroassociative pairs. BAM encoding and decoding are combined in the adaptive BAM, which extends global bidirectional stability to real-time unsupervised learning

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:18 ,  Issue: 1 )