Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method
This work addresses the stability study for stochastic cellular neural networks with time-varying delays. By utilizing the new research technique of the fixed point theory, we find some new and concise sufficient conditions ensuring the existence and uniqueness as well as mean-square global exponent...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/510358 |
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| _version_ | 1832548895266177024 |
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| author | Tianxiang Yao Xianghong Lai |
| author_facet | Tianxiang Yao Xianghong Lai |
| author_sort | Tianxiang Yao |
| collection | DOAJ |
| description | This work addresses the stability study for stochastic cellular neural networks with time-varying delays. By utilizing the new research technique of the fixed point theory, we find some new and concise sufficient conditions ensuring the existence and uniqueness as well as mean-square global exponential stability of the solution. The presented algebraic stability criteria are easily checked and do not require the differentiability of delays. The paper is finally ended with an example to show the effectiveness of the obtained results. |
| format | Article |
| id | doaj-art-7db5f6597a3d4deaa2b5cf7736454c3c |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-7db5f6597a3d4deaa2b5cf7736454c3c2025-02-03T06:12:45ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/510358510358Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point MethodTianxiang Yao0Xianghong Lai1Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, 210044, ChinaSchool of Economics & Management, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaThis work addresses the stability study for stochastic cellular neural networks with time-varying delays. By utilizing the new research technique of the fixed point theory, we find some new and concise sufficient conditions ensuring the existence and uniqueness as well as mean-square global exponential stability of the solution. The presented algebraic stability criteria are easily checked and do not require the differentiability of delays. The paper is finally ended with an example to show the effectiveness of the obtained results.http://dx.doi.org/10.1155/2014/510358 |
| spellingShingle | Tianxiang Yao Xianghong Lai Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method Journal of Applied Mathematics |
| title | Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method |
| title_full | Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method |
| title_fullStr | Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method |
| title_full_unstemmed | Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method |
| title_short | Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method |
| title_sort | mean square exponential stability analysis of stochastic neural networks with time varying delays via fixed point method |
| url | http://dx.doi.org/10.1155/2014/510358 |
| work_keys_str_mv | AT tianxiangyao meansquareexponentialstabilityanalysisofstochasticneuralnetworkswithtimevaryingdelaysviafixedpointmethod AT xianghonglai meansquareexponentialstabilityanalysisofstochasticneuralnetworkswithtimevaryingdelaysviafixedpointmethod |