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- Publisher Website: 10.1109/ICCA.2007.4376399
- Scopus: eid_2-s2.0-44349191614
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Conference Paper: Global exponential estimates of stochastic Cohen-Grossberg neural networks with time delay
Title | Global exponential estimates of stochastic Cohen-Grossberg neural networks with time delay |
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Authors | |
Keywords | Cohen-Grossberg Neural Networks Exponential Estimates Linear Matrix Inequality Stochastic Disturbance Time Delay |
Issue Date | 2008 |
Citation | 2007 Ieee International Conference On Control And Automation, Icca, 2008, p. 459-464 How to Cite? |
Abstract | This paper is concerned with the exponential estimating problem for Cohen-Grossberg neural networks with time delay and stochastic disturbance. A sufficient condition, which does not only guarantee the global exponential stability but also provides more exact characterization on the decay rate and the coefficient, is established in terms of the Lyapunov-Krasovskii functional approach and the linear matrix inequality (LMI) technique. The estimates of the decay rate and the coefficient are obtained by solving a set of LMIs, which can be checked easily by effective algorithms. In addition, slack matrices are introduced to reduce the conservatism of the condition. A numerical example is provided to illustrate the effectiveness of the theoretical results. © 2007 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/158983 |
References |
DC Field | Value | Language |
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dc.contributor.author | Zhan, S | en_US |
dc.contributor.author | Lam, J | en_US |
dc.date.accessioned | 2012-08-08T09:04:57Z | - |
dc.date.available | 2012-08-08T09:04:57Z | - |
dc.date.issued | 2008 | en_US |
dc.identifier.citation | 2007 Ieee International Conference On Control And Automation, Icca, 2008, p. 459-464 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/158983 | - |
dc.description.abstract | This paper is concerned with the exponential estimating problem for Cohen-Grossberg neural networks with time delay and stochastic disturbance. A sufficient condition, which does not only guarantee the global exponential stability but also provides more exact characterization on the decay rate and the coefficient, is established in terms of the Lyapunov-Krasovskii functional approach and the linear matrix inequality (LMI) technique. The estimates of the decay rate and the coefficient are obtained by solving a set of LMIs, which can be checked easily by effective algorithms. In addition, slack matrices are introduced to reduce the conservatism of the condition. A numerical example is provided to illustrate the effectiveness of the theoretical results. © 2007 IEEE. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | 2007 IEEE International Conference on Control and Automation, ICCA | en_US |
dc.subject | Cohen-Grossberg Neural Networks | en_US |
dc.subject | Exponential Estimates | en_US |
dc.subject | Linear Matrix Inequality | en_US |
dc.subject | Stochastic Disturbance | en_US |
dc.subject | Time Delay | en_US |
dc.title | Global exponential estimates of stochastic Cohen-Grossberg neural networks with time delay | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Lam, J:james.lam@hku.hk | en_US |
dc.identifier.authority | Lam, J=rp00133 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1109/ICCA.2007.4376399 | en_US |
dc.identifier.scopus | eid_2-s2.0-44349191614 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-44349191614&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.spage | 459 | en_US |
dc.identifier.epage | 464 | en_US |
dc.identifier.scopusauthorid | Zhan, S=15052621300 | en_US |
dc.identifier.scopusauthorid | Lam, J=7201973414 | en_US |