A new algorithm of selecting the radial basis function networks center

Author

Wang, Hong-rui ; Wang, Hong-Bin ; Wei, Li-Xin ; LI, Ying

Author_Institution

Dept. of Electr. Eng., Yanshan Univ., Qinhuangdao, China

Volume

4

fYear

2002

fDate

4-5 Nov. 2002

Firstpage

1801

Abstract

The selecting of the radial basis function center is a key factor that influences the performance of networks. In this paper we first introduce briefly the fuzzy c-mean algorithm and k-nearest-neighbor algorithm as to the selection of the radial basis function center, and then we present a δ-nearest-neighbor cluster algorithm which combines the k-nearest-neighbor algorithm with fuzzy c-mean algorithm. Finally, we demonstrate the performance results for dynamic system identification via simulations.

Keywords

fuzzy set theory; identification; learning (artificial intelligence); radial basis function networks; RBF neural networks; dynamic system identification; fuzzy c-mean algorithm; nearest-neighbor cluster algorithm; parameter learning; radial basis function center; radial basis function neural networks; Algorithm design and analysis; Clustering algorithms; Maximum likelihood estimation; Neural networks; Pathology; Pattern recognition; Radial basis function networks; Signal processing algorithms; System identification; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on

Print_ISBN

0-7803-7508-4

Type

conf

DOI

10.1109/ICMLC.2002.1175350

Filename

1175350