Binary Factorization by Neural Autoassociators.

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F03%3A06030150" target="_blank" >RIV/67985807:_____/03:06030150 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Binary Factorization by Neural Autoassociators.

Original language description

In this paper we demonstrate that Hebbian learning in Hopfield-like neural network is a natural procedure for binary factorization. Due to this learning, factors become the attractors of network dynamics. The neurodynamics is analyzed by Single-Step approximation, which is known to be rather accurate for sparsely encoded Hopfield-network. The accuracy of Single-Step approximation is confirmed by computer simulations.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

BD - Information theory

OECD FORD branch

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Project

<a href="/en/project/LN00B096" target="_blank" >LN00B096: Center for Applied Cybernetics</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2003

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Artificial Intelligence and Applications.

ISBN

0-88986-390-3

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

649-653

Publisher name

ACTA Press

Place of publication

Zürich

Event location

Benalmadena [ES]

Event date

Sep 8, 2003

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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