New Results on Passivity Analysis of Delayed Discrete-Time Stochastic Neural Networks
The problem of passivity analysis for a class of discrete-time stochastic neural networks (DSNNs) with time-varying interval delay is investigated. The delay-dependent sufficient criteria are derived in terms of linear matrix inequalities (LMIs). The results are shown to be generalization of some pr...
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| Format: | Article |
| Language: | English |
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Wiley
2009-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2009/139671 |
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| _version_ | 1850212976612605952 |
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| author | Jianjiang Yu |
| author_facet | Jianjiang Yu |
| author_sort | Jianjiang Yu |
| collection | DOAJ |
| description | The problem of passivity analysis for a class of discrete-time stochastic neural networks (DSNNs) with time-varying interval delay is investigated. The delay-dependent sufficient criteria are derived in terms of linear matrix inequalities (LMIs). The results are shown to be generalization of some previous results and are less conservative than the existing works. Meanwhile, the computational complexity of the obtained stability conditions is reduced because less variables are involved. Two numerical examples are given to show the effectiveness and the benefits of the proposed method. |
| format | Article |
| id | doaj-art-8c46aeb7019d4e0c962e56976eecfb24 |
| institution | OA Journals |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2009-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-8c46aeb7019d4e0c962e56976eecfb242025-08-20T02:09:13ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2009-01-01200910.1155/2009/139671139671New Results on Passivity Analysis of Delayed Discrete-Time Stochastic Neural NetworksJianjiang Yu0School of Information Science and Technology, Yancheng Teachers University, Yancheng 224002, ChinaThe problem of passivity analysis for a class of discrete-time stochastic neural networks (DSNNs) with time-varying interval delay is investigated. The delay-dependent sufficient criteria are derived in terms of linear matrix inequalities (LMIs). The results are shown to be generalization of some previous results and are less conservative than the existing works. Meanwhile, the computational complexity of the obtained stability conditions is reduced because less variables are involved. Two numerical examples are given to show the effectiveness and the benefits of the proposed method.http://dx.doi.org/10.1155/2009/139671 |
| spellingShingle | Jianjiang Yu New Results on Passivity Analysis of Delayed Discrete-Time Stochastic Neural Networks Discrete Dynamics in Nature and Society |
| title | New Results on Passivity Analysis of Delayed Discrete-Time Stochastic Neural Networks |
| title_full | New Results on Passivity Analysis of Delayed Discrete-Time Stochastic Neural Networks |
| title_fullStr | New Results on Passivity Analysis of Delayed Discrete-Time Stochastic Neural Networks |
| title_full_unstemmed | New Results on Passivity Analysis of Delayed Discrete-Time Stochastic Neural Networks |
| title_short | New Results on Passivity Analysis of Delayed Discrete-Time Stochastic Neural Networks |
| title_sort | new results on passivity analysis of delayed discrete time stochastic neural networks |
| url | http://dx.doi.org/10.1155/2009/139671 |
| work_keys_str_mv | AT jianjiangyu newresultsonpassivityanalysisofdelayeddiscretetimestochasticneuralnetworks |