Some special properties of G A- and LS-based neural learning method

Title: Some special properties of G A- and LS-based neural learning method
Creator: Ghosh, Ranadhir
Date: 2005
Type: Text; Journal article
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/58097
Identifier: vital:323
Identifier: ISSN:0334-1860
Abstract: Many works in the area of hybrid neural learning algorithms combine global and local based method for artificial neural network. In this paper, we discuss some special properties of a hybrid neural learning algorithm that combines the GA based method with least square based methods such as QR factorization. We look at different types of learning properties of this new hybrid algorithm, such as time complexity, convergence property, and the stability of the algorithm.; C1
Publisher: Freund Publishing House, Ltd.
Relation: Journal of Intelligent Systems Vol. 14, no. 4 (2005), p. 289-319
Rights: Copyright Freund Publishing House, Ltd.
Rights: This metadata is freely available under a CCO license
Subject: 0801 Artificial Intelligence and Image Processing; Convergence of numerical methods; Learning algorithms; Neural networks; Hybrid algorithms; Least square based methods; Neural learning methods; Learning systems
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