Detail publikace

Analysis of Algorithms for Radial Basis Function Neural Network

ŠŤASTNÝ, J. ŠKORPIL, V.

Originální název

Analysis of Algorithms for Radial Basis Function Neural Network

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

The contribution 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 a using of learning algorithms LMS (Least Mean Square) and gradient algorithms and results obtained by a 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.

Klíčová slova

Radial basis function, Learning algorithm, Neuron, Hidden layer

Autoři

ŠŤASTNÝ, J.; ŠKORPIL, V.

Rok RIV

2007

Vydáno

1. 9. 2007

Nakladatel

Springer

ISSN

1861-2288

Periodikum

Personal Wireless Communications

Ročník

2007

Číslo

1

Stát

Spojené státy americké

Strany od

54

Strany do

62

Strany počet

9

BibTex

@article{BUT48693,
  author="Jiří {Šťastný} and Vladislav {Škorpil}",
  title="Analysis of Algorithms for Radial Basis Function Neural Network",
  journal="Personal Wireless Communications",
  year="2007",
  volume="2007",
  number="1",
  pages="54--62",
  issn="1861-2288"
}