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http://bura.brunel.ac.uk/handle/2438/4951
Title: | On global asymptotic stability of neural networks with discrete and distributed delays |
Authors: | Wang, Z Liu, Y Liu, X |
Keywords: | Neural networks;Distributed delays;Discrete delays;Lyapunov–Krasovskii functional;Global asymptotic stability;Linear matrix inequality |
Issue Date: | 2005 |
Publisher: | Elsevier |
Citation: | Physics Letters A, 345(4-6): 299-308, Oct 2005 |
Abstract: | In this Letter, the global asymptotic stability analysis problem is investigated for a class of neural networks with discrete and distributed time-delays. The purpose of the problem is to determine the asymptotic stability by employing some easy-to-test conditions. It is shown, via the Lyapunov–Krasovskii stability theory, that the class of neural networks under consideration is globally asymptotically stable if a quadratic matrix inequality involving several parameters is feasible. Furthermore, a linear matrix inequality (LMI) approach is exploited to transform the addressed stability analysis problem into a convex optimization problem, and sufficient conditions for the neural networks to be globally asymptotically stable are then derived in terms of a linear matrix inequality, which can be readily solved by using the Matlab LMI toolbox. Two numerical examples are provided to show the usefulness of the proposed global stability condition. |
Description: | This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2005 Elsevier Ltd. |
URI: | http://bura.brunel.ac.uk/handle/2438/4951 |
DOI: | http://dx.doi.org/10.1016/j.physleta.2005.07.025 |
ISSN: | 0375-9601 |
Appears in Collections: | Computer Science Dept of Computer Science Research Papers |
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