Detail publikace

Analysis of Algorithms for Radial Basis Function Neural Network. Springer Verlag:

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

2007

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"
}