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ŠKORPIL, V. ŠŤASTNÝ, J.
Originální název
Analysis of Algorithms for Radial Basis Function Neural Network. Springer Verlag:
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Radial basis function, Learning algorithm, Neuron, Hidden layer.
Autoři
ŠKORPIL, V.; ŠŤASTNÝ, J.
Rok RIV
2007
Vydáno
7. 9. 2007
Nakladatel
Springer
Místo
Prague
ISSN
1571-5736
Periodikum
Mobile and Wireless Communication Networks
Ročník
Číslo
1
Stát
Spojené státy americké
Strany od
54
Strany do
62
Strany počet
9
BibTex
@article{BUT47411, author="Vladislav {Škorpil} and Jiří {Šťastný}", title="Analysis of Algorithms for Radial Basis Function Neural Network. Springer Verlag:", journal="Mobile and Wireless Communication Networks", year="2007", volume="2007", number="1", pages="54--62", issn="1571-5736" }