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New preprocessing methods for holographic neural networks (CROSBI ID 516089)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Manger, Robert ; Souček, Branko New preprocessing methods for holographic neural networks // Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms (ANNGA '93) / Albrecht, R.F ; Reeves, C.R ; Steele, N.C. (ur.). Beč: Springer, 1993. str. 190-197-x

Podaci o odgovornosti

Manger, Robert ; Souček, Branko

engleski

New preprocessing methods for holographic neural networks

We propose two new methods for preprocessing of stimulus data in holographic neural networks. The first method achieves optimal data symmetrization, and it is based on estimating the actual distributions of elements within a stimulus vector. The second method serves for data expansion, and it relies on sine and cosine functions to produce dummy stimulus elements. We describe an implementation of our methods and report on some experiments. Our proposals improve the applicability of holographic networks. Namely, symmetrization assures accuracy in reproducing learned stimulus-response associations, while expansion increases learning capacity.

holographic neural networks; data preprocessing; stimulus expansion; stimulus symmetrization

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Podaci o prilogu

190-197-x.

1993.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms (ANNGA '93)

Albrecht, R.F ; Reeves, C.R ; Steele, N.C.

Beč: Springer

Podaci o skupu

International Confeerence on Artificial Neural Nets and Genetic Algorithms (ANNGA '93)

predavanje

14.04.1993-16.04.1993

Innsbruck, Austrija

Povezanost rada

Računarstvo, Matematika