The optimal encodings for biased association in linear associative memories

In this paper, optimal encoding schemes for linear associative memories are derived for biased association under both the white-noise and colored-noise situations. Analysis and simulation results all show that the biased encodings thus derived are optimal and superior to existing models in their performance. Together with the Wee-Kohonen unbiased encoding, the study settles the optimality issue of linear associative memories and enhances their practicalities.

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