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DC Field | Value | Language |
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dc.contributor.author | Wang, Z | - |
dc.contributor.author | Liu, Y | - |
dc.contributor.author | Liu, X | - |
dc.date.accessioned | 2011-04-04T10:42:26Z | - |
dc.date.available | 2011-04-04T10:42:26Z | - |
dc.date.issued | 2005 | - |
dc.identifier.citation | Physics Letters A, 345(4-6): 299-308, Oct 2005 | en_US |
dc.identifier.issn | 0375-9601 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/4951 | - |
dc.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. | en_US |
dc.description.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. | en_US |
dc.description.sponsorship | This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Nuffield Foundation of the UK under Grant NAL/00630/G, and the Alexander von Humboldt Foundation of Germany. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Distributed delays | en_US |
dc.subject | Discrete delays | en_US |
dc.subject | Lyapunov–Krasovskii functional | en_US |
dc.subject | Global asymptotic stability | en_US |
dc.subject | Linear matrix inequality | en_US |
dc.title | On global asymptotic stability of neural networks with discrete and distributed delays | en_US |
dc.type | Research Paper | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/j.physleta.2005.07.025 | - |
Appears in Collections: | Computer Science Dept of Computer Science Research Papers |
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