Global robust exponential stability for Hopfield neural networks with non-Lipschitz activation functions
This paper is concerned with the problem of the global robust exponential stability for Hopfield neural networks with norm-bounded parameter uncertainties and inverse Holder neuron activation functions. By ¨ applying Brouwer degree properties and some analysis techniques, the existence and uniquenes...
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| Datum: | 2012 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
Інститут математики НАН України
2012
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| Schriftenreihe: | Нелінійні коливання |
| Online Zugang: | http://dspace.nbuv.gov.ua/handle/123456789/175586 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Zitieren: | Global robust exponential stability for Hopfield neural networks with non-Lipschitz activation functions / Hongtao Yu, Huaiqin Wu // Нелінійні коливання. — 2012. — Т. 15, № 1. — С. 127-138. — Бібліогр.: 26 назв. — англ. |
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Digital Library of Periodicals of National Academy of Sciences of Ukraine| Zusammenfassung: | This paper is concerned with the problem of the global robust exponential stability for Hopfield neural networks with norm-bounded parameter uncertainties and inverse Holder neuron activation functions. By ¨ applying Brouwer degree properties and some analysis techniques, the existence and uniqueness of the equilibrium point are investigated. Based on the Lyapunov stability theory, a global robust exponential stability criterion is derived in terms of linear matrix inequality (LMI). Two numerical examples are provided to demonstrate the effectiveness and validity of the proposed robust stability results. |
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