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Statements

Subject Item
n2:RIV%2F68407700%3A21460%2F07%3A12132181%21RIV08-MSM-21460___
rdf:type
n12:Vysledek skos:Concept
dcterms:description
We investigate an artificial neural network model with a modified Hebb rule. It is an auto-associative neural network similar to the Hopfield model and to the Willshaw model. It has properties of both of these models. Another property is that the patterns are sparsely coded and are stored in cycles of synchronous neural activities. The cycles of activity for some ranges of parameter increase the capacity of the model. We discuss basic properties of the model and some of the implementation issues, namely optimizing of the algorithms. We describe the modification of the Hebb learning rule, the learning algorithm, the generation of patterns, decomposition of patterns into cycles and pattern recall. Práce studuje originální design neuronové sítě. Ta je inspirovaná Hopfieldovou a Willshawovou sítí s použitím Hebbova pravidla modifikovaného tak, aby cyklicky aktivovalo skupiny neuronů. Práce prezentuje implementaci a odhady kapacity této sítě. We investigate an artificial neural network model with a modified Hebb rule. It is an auto-associative neural network similar to the Hopfield model and to the Willshaw model. It has properties of both of these models. Another property is that the patterns are sparsely coded and are stored in cycles of synchronous neural activities. The cycles of activity for some ranges of parameter increase the capacity of the model. We discuss basic properties of the model and some of the implementation issues, namely optimizing of the algorithms. We describe the modification of the Hebb learning rule, the learning algorithm, the generation of patterns, decomposition of patterns into cycles and pattern recall.
dcterms:title
Záznam paměťových stop v neuronové síti pomocí řídkého kódování a cyklické aktivace Pattern Storage in a Sparsely Coded Neural Network with Cyclic Activation Pattern Storage in a Sparsely Coded Neural Network with Cyclic Activation
skos:prefLabel
Pattern Storage in a Sparsely Coded Neural Network with Cyclic Activation Pattern Storage in a Sparsely Coded Neural Network with Cyclic Activation Záznam paměťových stop v neuronové síti pomocí řídkého kódování a cyklické aktivace
skos:notation
RIV/68407700:21460/07:12132181!RIV08-MSM-21460___
n3:strany
257;263
n3:aktivita
n18:Z
n3:aktivity
Z(MSM6840770012)
n3:cisloPeriodika
1-3
n3:dodaniDat
n7:2008
n3:domaciTvurceVysledku
n14:1152548
n3:druhVysledku
n5:J
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n15:predkladatel
n3:idSjednocenehoVysledku
440829
n3:idVysledku
RIV/68407700:21460/07:12132181
n3:jazykVysledku
n4:eng
n3:klicovaSlova
Hebb rule; Hopfield network; auto-associative neural network
n3:klicoveSlovo
n10:Hopfield%20network n10:auto-associative%20neural%20network n10:Hebb%20rule
n3:kodStatuVydavatele
GB - Spojené království Velké Británie a Severního Irska
n3:kontrolniKodProRIV
[7034E28171C9]
n3:nazevZdroje
Biosystems
n3:obor
n6:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
3
n3:rokUplatneniVysledku
n7:2007
n3:svazekPeriodika
89
n3:tvurceVysledku
Maršálek, Petr Kuriscak, E. Stroffek, J.
n3:zamer
n13:MSM6840770012
s:issn
0303-2647
s:numberOfPages
7
n17:organizacniJednotka
21460