Publication result detail

Analysis of Algorithms for Radial Basis Function Neural Network

ŠŤASTNÝ, J.; ŠKORPIL, V.

Original Title

Analysis of Algorithms for Radial Basis Function Neural Network

English Title

Analysis of Algorithms for Radial Basis Function Neural Network

Type

WoS Article

Original Abstract

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.

English abstract

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.

Keywords

Radial basis function, Learning algorithm, Neuron, Hidden layer

Key words in English

Radial basis function, Learning algorithm, Neuron, Hidden layer

Authors

ŠŤASTNÝ, J.; ŠKORPIL, V.

RIV year

2010

Released

01.09.2007

Publisher

Springer

ISBN

1861-2288

Periodical

Personal Wireless Communications

Volume

2007

Number

1

State

United States of America

Pages from

54

Pages to

62

Pages count

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"
}