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Construction of a Distributed Associative Memory on the Basis of Bayes Discriminant Rule
February 1981 (vol. 3 no. 2)
pp. 210-214
Kenji Murakami, Department of Electronics Engineering, Ehime University, Matsuyama, Japan.
Tsunehiro Aibara, Department of Electronics Engineering, Ehime University, Matsuyama, Japan.
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.
Citation:
Kenji Murakami, Tsunehiro Aibara, "Construction of a Distributed Associative Memory on the Basis of Bayes Discriminant Rule," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 3, no. 2, pp. 210-214, Feb. 1981, doi:10.1109/TPAMI.1981.4767083
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