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Construction of a Distributed Associative Memory on the Basis of Bayes Discriminant Rule

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2 Author(s)
Murakami, Kenji ; Department of Electronics Engineering, Ehime University, Matsuyama, Japan. ; Aibara, Tsunehiro

The purpose of this correspondence is to propose a new construction method of distributed associative memory which operates with discrete-valued signals. In this method, memorized pairs of vectors (cue vectors and data vectors) are recorded in the form of a matrix W and a vector T. From an input vector X, the data vector is recalled by an operation u(XW + T) where X is a cue vector or a noisy cue vector. and u is a quantizing function. The methods of memorization and recall are similar to the Associatron; however, the proposed model can recall the data vectors optimally in Bayesian sense even when noisy cue vectors are given as the input vectors.

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:PAMI-3 ,  Issue: 2 )