title: Construction of a distributed associative memory on the basis of bayes discriminant rule.
abstract: 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.
authors.affiliation: Department of Electronics Engineering, Ehime University, Matsuyama, Japan.
authors.forename: K
authors.initials: K
authors.lastname: Murakami
authors.forename: T
authors.initials: T
authors.lastname: Aibara