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...
Збережено в:
| Дата: | 2012 |
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| Автори: | , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Інститут математики НАН України
2012
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| Назва видання: | Нелінійні коливання |
| Онлайн доступ: | http://dspace.nbuv.gov.ua/handle/123456789/175586 |
| Теги: |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | 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. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of Ukraine| Резюме: | 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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