Stochastic Passivity of Uncertain Neural Networks with Time-Varying Delays
The passivity problem is investigated for a class of stochastic uncertain neural networks with time-varying delay as well as generalized activation functions. By constructing appropriate Lyapunov-Krasovskii functionals, and employing Newton-Leibniz formulation, the free-weighting matrix method, and...
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| Format: | Article |
| Language: | English |
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Wiley
2009-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2009/725846 |
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| _version_ | 1832548938353213440 |
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| author | Jianting Zhou Qiankun Song Jianxi Yang |
| author_facet | Jianting Zhou Qiankun Song Jianxi Yang |
| author_sort | Jianting Zhou |
| collection | DOAJ |
| description | The passivity problem is investigated for a class of stochastic uncertain neural networks with time-varying
delay as well as generalized activation functions. By constructing appropriate Lyapunov-Krasovskii functionals,
and employing Newton-Leibniz formulation, the free-weighting matrix method, and stochastic analysis technique, a
delay-dependent criterion for checking the passivity of the addressed neural networks is established in terms of linear
matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. An example
with simulation is given to show the effectiveness and less conservatism of the proposed criterion. It is noteworthy that
the traditional assumptions on the differentiability of the time-varying delays and the boundedness of its derivative are
removed. |
| format | Article |
| id | doaj-art-29f43fe76c4c44778035ea54bd858ce4 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2009-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-29f43fe76c4c44778035ea54bd858ce42025-02-03T06:12:32ZengWileyAbstract and Applied Analysis1085-33751687-04092009-01-01200910.1155/2009/725846725846Stochastic Passivity of Uncertain Neural Networks with Time-Varying DelaysJianting Zhou0Qiankun Song1Jianxi Yang2College of Civil Engineering and Architecture, Chongqing Jiaotong University, Chongqing 400074, ChinaDepartment of Mathematics, Chongqing Jiaotong University, Chongqing 400074, ChinaCollege of Civil Engineering and Architecture, Chongqing Jiaotong University, Chongqing 400074, ChinaThe passivity problem is investigated for a class of stochastic uncertain neural networks with time-varying delay as well as generalized activation functions. By constructing appropriate Lyapunov-Krasovskii functionals, and employing Newton-Leibniz formulation, the free-weighting matrix method, and stochastic analysis technique, a delay-dependent criterion for checking the passivity of the addressed neural networks is established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. An example with simulation is given to show the effectiveness and less conservatism of the proposed criterion. It is noteworthy that the traditional assumptions on the differentiability of the time-varying delays and the boundedness of its derivative are removed.http://dx.doi.org/10.1155/2009/725846 |
| spellingShingle | Jianting Zhou Qiankun Song Jianxi Yang Stochastic Passivity of Uncertain Neural Networks with Time-Varying Delays Abstract and Applied Analysis |
| title | Stochastic Passivity of Uncertain Neural Networks with Time-Varying Delays |
| title_full | Stochastic Passivity of Uncertain Neural Networks with Time-Varying Delays |
| title_fullStr | Stochastic Passivity of Uncertain Neural Networks with Time-Varying Delays |
| title_full_unstemmed | Stochastic Passivity of Uncertain Neural Networks with Time-Varying Delays |
| title_short | Stochastic Passivity of Uncertain Neural Networks with Time-Varying Delays |
| title_sort | stochastic passivity of uncertain neural networks with time varying delays |
| url | http://dx.doi.org/10.1155/2009/725846 |
| work_keys_str_mv | AT jiantingzhou stochasticpassivityofuncertainneuralnetworkswithtimevaryingdelays AT qiankunsong stochasticpassivityofuncertainneuralnetworkswithtimevaryingdelays AT jianxiyang stochasticpassivityofuncertainneuralnetworkswithtimevaryingdelays |