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author:

Ma, X. (Ma, X..) [1] | Chen, X.-C. (Chen, X.-C..) [2] | Wang, S.-B. (Wang, S.-B..) [3]

Indexed by:

Scopus PKU CSCD

Abstract:

Learning sample selection has the very tremendous influence to the generalization ability of the neural network. This paper proposed that the learning sample selection should consider the characteristics of the non-linear object approached. A method of selecting learning samples based on the uniform design and clustering theory is discussed. The result of application shows that the effective selection of the learning samples can improve the generalization ability of the neural networks.

Keyword:

Clustering theory; Generalization ability; Neural network; Radial basis function (RBF); Sample selection; Uniform design

Community:

  • [ 1 ] [Ma, X.]Automation-Technological Company Limited, Fuzhou University, Fuzhou 350002, China
  • [ 2 ] [Chen, X.-C.]Automation-Technological Company Limited, Fuzhou University, Fuzhou 350002, China
  • [ 3 ] [Wang, S.-B.]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350002, China

Reprint 's Address:

  • [Ma, X.]Automation-Technological Company Limited, Fuzhou University, Fuzhou 350002, China

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Source :

Pattern Recognition and Artificial Intelligence

ISSN: 1003-6059

Year: 2005

Issue: 2

Volume: 18

Page: 252-255

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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