Exponential stability of stochastic neural networks with both markovian jump parameters and mixed time delays
In this paper, the problem of exponential stability is investigated for a class of stochastic neural networks with both Markovian jump parameters and mixed time delays. The jumping parameters are modeled as a continuous-time finite-state Markov chain. Based on a Lyapunov-Krasovskii functional and th...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society. - 1996. - 41(2011), 2 vom: 15. Apr., Seite 341-53
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| 1. Verfasser: |
Zhu, Quanxin
(VerfasserIn) |
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| Weitere Verfasser: |
Cao, Jinde |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2011
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
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