Determination of the appropriate node function of NNs by using the cascade-correlation algorithms

Weishui Wan, Kotaro Hirasawa, Junichi Murata, Chunzhi Jin, Jinglu Hu

Research output: Contribution to conferencePaper

Abstract

How to determine the appropriate or optimal activation function in the neural networks for a specific learning samples remains open. In this paper the cascade-correlation algorithm which is an efficient constructive algorithm is used after implementation of some kinds of clustering algorithms to produce a modular network structure as a surrogate of activation node functions in the radial basis function (RBF) networks. In this way great improvement on the convergence rate of training algorithms and better approximation are achieved. Simulations with the two-spiral data sets proved the above assertion.

Original languageEnglish
Pages1177-1182
Number of pages6
Publication statusPublished - 2000 Dec 1
Event26th Annual Conference of the IEEE Electronics Society IECON 2000 - Nagoya, Japan
Duration: 2000 Oct 222000 Oct 28

Conference

Conference26th Annual Conference of the IEEE Electronics Society IECON 2000
CountryJapan
CityNagoya
Period00/10/2200/10/28

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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    Wan, W., Hirasawa, K., Murata, J., Jin, C., & Hu, J. (2000). Determination of the appropriate node function of NNs by using the cascade-correlation algorithms. 1177-1182. Paper presented at 26th Annual Conference of the IEEE Electronics Society IECON 2000, Nagoya, Japan.