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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F07%3APU71860%21RIV10-MSM-26220___
rdf:type
n18:Vysledek skos:Concept
dcterms:description
This paper describes the analysis of algorithms for the hidden layer construction of network and for learning of the Radial Basis Function neural Network (RBFN). We compared results obtained by using of learning algorithms LMS (Least Mean Square) and Gradient Algorithms (GA) and results are obtained by using of algorithms APC-III and K-means for hidden layer contruction of neural network. The principles and algorithms given below have been used in an application for object classification that was developed at Brno University of Technology. This solution is suitable for the research of personal wireless communications and similar systems. This paper describes the analysis of algorithms for the hidden layer construction of network and for learning of the Radial Basis Function neural Network (RBFN). We compared results obtained by using of learning algorithms LMS (Least Mean Square) and Gradient Algorithms (GA) and results are obtained by using of algorithms APC-III and K-means for hidden layer contruction of neural network. The principles and algorithms given below have been used in an application for object classification that was developed at Brno University of Technology. This solution is suitable for the research of personal wireless communications and similar systems.
dcterms:title
Analysis of Algorithms for Radial Basis Function Neural Network. Springer Verlag: Analysis of Algorithms for Radial Basis Function Neural Network. Springer Verlag:
skos:prefLabel
Analysis of Algorithms for Radial Basis Function Neural Network. Springer Verlag: Analysis of Algorithms for Radial Basis Function Neural Network. Springer Verlag:
skos:notation
RIV/00216305:26220/07:PU71860!RIV10-MSM-26220___
n3:aktivita
n4:Z n4:P
n3:aktivity
P(2E06034), P(GA102/07/1503), Z(MSM0021630513)
n3:cisloPeriodika
1
n3:dodaniDat
n16:2010
n3:domaciTvurceVysledku
n13:4746392 n13:1250019
n3:druhVysledku
n17:J
n3:duvernostUdaju
n7:S
n3:entitaPredkladatele
n5:predkladatel
n3:idSjednocenehoVysledku
409435
n3:idVysledku
RIV/00216305:26220/07:PU71860
n3:jazykVysledku
n15:eng
n3:klicovaSlova
Radial basis function, Learning algorithm, Neuron, Hidden layer.
n3:klicoveSlovo
n12:Hidden%20layer. n12:Learning%20algorithm n12:Neuron n12:Radial%20basis%20function
n3:kodStatuVydavatele
US - Spojené státy americké
n3:kontrolniKodProRIV
[C376906016E4]
n3:nazevZdroje
Mobile and Wireless Communication Networks
n3:obor
n19:JA
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n11:2E06034 n11:GA102%2F07%2F1503
n3:rokUplatneniVysledku
n16:2007
n3:svazekPeriodika
2007
n3:tvurceVysledku
Šťastný, Jiří Škorpil, Vladislav
n3:wos
000250717300005
n3:zamer
n9:MSM0021630513
s:issn
1571-5736
s:numberOfPages
9
n14:organizacniJednotka
26220