Magnified gradient function in adaptive learning : The MGFPROP algorithm

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

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)42-43
Journal / PublicationElectronics Letters
Volume37
Issue number1
Publication statusPublished - 4 Jan 2001

Abstract

A new algorithm is proposed to solve the `flat spot' problem in back-propagation neural networks by magnifying the gradient function. Simulation results show that, in terms of the convergence rate and the percentage of global convergence, the new algorithm consistently outperforms other traditional methods.

Citation Format(s)

Magnified gradient function in adaptive learning : The MGFPROP algorithm. / Ng, Sin-Chun; Cheung, Chi-Chung; Leung, Shu-Hung.

In: Electronics Letters, Vol. 37, No. 1, 04.01.2001, p. 42-43.

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