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

Weishui Wan, Kotaro Hirasawa, Junichi Murata, Chunzhi Jin, Takayuki Furuzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
Pages1177-1182
Number of pages6
Volume2
Publication statusPublished - 2000
Externally publishedYes
Event26th Annual Conference of the IEEE Electronics Society IECON 2000 - Nagoya
Duration: 2000 Oct 222000 Oct 28

Other

Other26th Annual Conference of the IEEE Electronics Society IECON 2000
CityNagoya
Period00/10/2200/10/28

    Fingerprint

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Wan, W., Hirasawa, K., Murata, J., Jin, C., & Furuzuki, T. (2000). Determination of the appropriate node function of NNs by using the cascade-correlation algorithms. In IECON Proceedings (Industrial Electronics Conference) (Vol. 2, pp. 1177-1182)