Nonlinear factorization in Hopfield-like neural networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F01%3A00001076" target="_blank" >RIV/61989100:27240/01:00001076 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Nonlinear factorization in Hopfield-like neural networks
Original language description
The problem of binary factorization of complex patterns in recurrent Hopfield-like neural network was studied by means of computer simulation. The network ability to perform a factorization was analyzed depending on the number and sparseness of factors mixed in presented patterns. Binary factorization in sparsely encoded Hopfield-like neural network is treated as efficient statistical method and as a functional model of hippocampal CA3 field.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA201%2F01%2F1192" target="_blank" >GA201/01/1192: Research of neural networks capability to provide nonlinear Boolean factor analysis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2001
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Digital Signal Processing and Multimedia Communications DSP-MCOM 2001
ISBN
80-89091-49-4
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
98-101
Publisher name
UPJŠ
Place of publication
Košice
Event location
Košice
Event date
Jan 1, 2001
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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