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Nearly optimal correlations for shift-invariant associative memories
Abstract:
The optical implementation of the Hopfield algorithm in shift-invariant holographic associative memories is based on the use of correlators with matched filters. However, it is well known that such correlators have poor discrimination. We propose nearly optimal correlation designs for associative memories based on correlation filters that have maximum discrimination ability. These new designs avoid large cross-correlation-peak terms caused by a mismatch between partial input and the fully stored information in the filter. These solutions rely on whitened spectra of the stored and the recalled information.Computer simulations are made of eight different combinations.
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