Fast Heuristic Global Learning algorithm for multilayer neural networks

Siu Yeung Cho, Tommy W.S. Chow

Research output: Journal PublicationArticlepeer-review

3 Citations (Scopus)

Abstract

This paper presents a novel Heuristic Global Learning (HER-GBL) algorithm for multilayer neural networks. The algorithm is based upon the least squares method to maintain the fast convergence speed, and the penalized optimization to solve the problem of local minima. The penalty term, defined as a Gaussian-type function of the weight, is to provide an uphill force to escape from local minima. As a result, the training performance is dramatically improved. The proposed HER-GBL algorithm yields excellent results in terms of convergence speed, avoidance of local minima and quality of solution.

Original languageEnglish
Pages (from-to)177-187
Number of pages11
JournalNeural Processing Letters
Volume9
Issue number2
DOIs
Publication statusPublished - 1999
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • General Neuroscience
  • Computer Networks and Communications
  • Artificial Intelligence

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