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Convergence criteria for a Hopfield-type artificial neural network

Goundar, R. and Vanualailai, Jito and Sharma, Bibhya N. (2008) Convergence criteria for a Hopfield-type artificial neural network. Nonlinear Studies, 15 (2). pp. 111-122. ISSN 1359-8678

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Abstract

Motivated by recent applications of the Lyapunov method in artificial neural networks, which could be considered as dynamical systems for which the convergence of system trajectories to equilibrium states is a necessity, we re-look at a well-known Krasovskii stability criterion pertaining to autonomous systems and then essentially use the same underlying idea to propose appropriate convergence criteria for autonomous system. We then apply the criteria to neural networks and discuss our results with respect to recent ones in the field.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
Depositing User: Ms Neha Harakh
Date Deposited: 11 Jan 2008 13:02
Last Modified: 10 Jul 2012 18:23
URI: http://repository.usp.ac.fj/id/eprint/173
UNSPECIFIED

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