Dong-Lih Denq

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Monte Carlo simulations of the continuous Moore-Penrose generalized inverse associative memory (Kohonen [l]) have shown that the noise-to-signal ratio is improved on recall in the autoassociative case as long as the number of vector pairs stored is less than the number of components per vector. In the heteroassociative case, however, the noise-to-signal(More)
Monte Carlo methods have been used to study the recall accuracy of three discrete distributed associative memory models: a discrete correlation matrix model (DCM), the Bayes discriminant rule model developed by Murakami and Aibara (MA), and a discrete version of the generalized inverse model of Kohonen (DGI). The key (input) and data (output) vectors have(More)
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