The bidirectional associative memory (BAM) is a powerful neural network paradigm that is well suited to optical implementation. The BAM is heteroassociative (of which autoassociative operation is a special case) and is guaranteed to converge to a stable final state regardless of the connection weight matrix used. The BAM is placed in a conceptual framework that facilitates comparison with other neural network models. Variations on the BAM such as the bidirectional optimal memory (BOM), the competitive BAM (CBAM), and the adaptive BAM (ABAM) indicate some of the interesting directions this simple structure may evolve, leading in a natural progression toward the power of a model such as the Carpenter-Grossberg ART. The simplicity of the BAM invites uncomplicated optical implementations. BAM designs based on optical matrix—vector multipliers (MVMs) and on volume holographic connections are presented. Spatial light modulator (SLM) device designs currently under development to support the MVM BAMs are given.
© 1987 Optical Society of AmericaFull Article | PDF Article
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