Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay
The problem of global exponential stability for recurrent neural networks with time-varying delay is investigated. By dividing the time delay interval [0,τ(t)] into K+1 dynamical subintervals, a new Lyapunov-Krasovskii functional is introduced; then, a novel linear-matrix-inequality (LMI-) based del...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2013/540951 |
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| _version_ | 1832545822739267584 |
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| author | Wenguang Luo Xiuling Wang Yonghua Liu Hongli Lan |
| author_facet | Wenguang Luo Xiuling Wang Yonghua Liu Hongli Lan |
| author_sort | Wenguang Luo |
| collection | DOAJ |
| description | The problem of global exponential stability for recurrent neural networks with time-varying delay is investigated. By dividing the time delay interval [0,τ(t)] into K+1 dynamical subintervals, a new Lyapunov-Krasovskii functional is introduced; then, a novel linear-matrix-inequality (LMI-) based delay-dependent exponential stability criterion is derived, which is less conservative than some previous literatures (Zhang et al., 2005; He et al., 2006; and Wu et al., 2008). An illustrate example is finally provided to show the effectiveness and the advantage of the proposed result. |
| format | Article |
| id | doaj-art-ee3cb8dd282b4ada8a16a89465cc5bca |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-ee3cb8dd282b4ada8a16a89465cc5bca2025-02-03T07:24:44ZengWileyAbstract and Applied Analysis1085-33751687-04092013-01-01201310.1155/2013/540951540951Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying DelayWenguang Luo0Xiuling Wang1Yonghua Liu2Hongli Lan3School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaSchool of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaSchool of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaSchool of Computer Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaThe problem of global exponential stability for recurrent neural networks with time-varying delay is investigated. By dividing the time delay interval [0,τ(t)] into K+1 dynamical subintervals, a new Lyapunov-Krasovskii functional is introduced; then, a novel linear-matrix-inequality (LMI-) based delay-dependent exponential stability criterion is derived, which is less conservative than some previous literatures (Zhang et al., 2005; He et al., 2006; and Wu et al., 2008). An illustrate example is finally provided to show the effectiveness and the advantage of the proposed result.http://dx.doi.org/10.1155/2013/540951 |
| spellingShingle | Wenguang Luo Xiuling Wang Yonghua Liu Hongli Lan Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay Abstract and Applied Analysis |
| title | Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay |
| title_full | Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay |
| title_fullStr | Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay |
| title_full_unstemmed | Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay |
| title_short | Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay |
| title_sort | novel global exponential stability criterion for recurrent neural networks with time varying delay |
| url | http://dx.doi.org/10.1155/2013/540951 |
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