Original contribution
Associative memory neural networks with concatenated vectors and nonzero diagonal terms

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Abstract

The effects of vector concatenation as well as that of eliminating the zero diagonal restriction of associative memory neural network matrices is analyzed. Extensive computer simulations seem to indicate that the use of concatenated vectors increases the storage capacity of the association matrices, beyond the accepted practical limit of 0.14N, N being the length of the stored vectors.

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Cited by (3)

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    1996, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

This work was initiated while the author was with Hughes Research Laboratories, Malibu, CA 90265.

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