On-line Successive Synthesis of Wavelet Networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

29 Scopus Citations
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Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)91-100
Journal / PublicationNeural Processing Letters
Volume7
Issue number2
Publication statusPublished - 1998

Abstract

An approach for the on-line synthesis of wavelet network using recursive least square (RLS) training is proposed. It is based on the concept of successive approximation of the system function to be learned. By using the Bayesian Information Criteria (BIC), the optimal number of wavelets is determined in the training process. Simulation results show that the proposed approach can approximate the unknown system function satisfactorily. Moreover, it can adapt to the changes in system parameters that off-line training cannot.

Research Area(s)

  • Network synthesis, Recursive least square training, Wavelet network

Citation Format(s)

On-line Successive Synthesis of Wavelet Networks. / Wong, Kwok-Wo; Leung, Andrew Chi-Sing.

In: Neural Processing Letters, Vol. 7, No. 2, 1998, p. 91-100.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal