State Estimation for Discrete-Time Stochastic Neural Networks with Mixed Delays
This paper investigates the analysis problem for stability of discrete-time neural networks (NNs) with discrete- and distribute-time delay. Stability theory and a linear matrix inequality (LMI) approach are developed to establish sufficient conditions for the NNs to be globally asymptotically stabl...
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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/10.1155/2014/209486 |
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| _version_ | 1832560622692204544 |
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| author | Liyuan Hou Hong Zhu Shouming Zhong Yong Zeng Lin Shi |
| author_facet | Liyuan Hou Hong Zhu Shouming Zhong Yong Zeng Lin Shi |
| author_sort | Liyuan Hou |
| collection | DOAJ |
| description | This paper investigates the analysis problem for stability of discrete-time neural networks (NNs) with discrete- and distribute-time delay. Stability theory and a linear matrix inequality (LMI) approach are developed to establish sufficient conditions for the NNs to be globally asymptotically stable and to design a state estimator for the discrete-time neural networks. Both the discrete delay and distribute delays employ decomposing the delay interval approach, and the Lyapunov-Krasovskii functionals (LKFs) are constructed on these intervals, such that a new stability criterion is proposed in terms of linear matrix inequalities (LMIs). Numerical examples are given to demonstrate the effectiveness of the proposed method and the applicability of the proposed method. |
| format | Article |
| id | doaj-art-c2173effd7524c19900e3c636ea2d609 |
| 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-c2173effd7524c19900e3c636ea2d6092025-02-03T01:27:10ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/209486209486State Estimation for Discrete-Time Stochastic Neural Networks with Mixed DelaysLiyuan Hou0Hong Zhu1Shouming Zhong2Yong Zeng3Lin Shi4School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaThis paper investigates the analysis problem for stability of discrete-time neural networks (NNs) with discrete- and distribute-time delay. Stability theory and a linear matrix inequality (LMI) approach are developed to establish sufficient conditions for the NNs to be globally asymptotically stable and to design a state estimator for the discrete-time neural networks. Both the discrete delay and distribute delays employ decomposing the delay interval approach, and the Lyapunov-Krasovskii functionals (LKFs) are constructed on these intervals, such that a new stability criterion is proposed in terms of linear matrix inequalities (LMIs). Numerical examples are given to demonstrate the effectiveness of the proposed method and the applicability of the proposed method.http://dx.doi.org/10.1155/2014/209486 |
| spellingShingle | Liyuan Hou Hong Zhu Shouming Zhong Yong Zeng Lin Shi State Estimation for Discrete-Time Stochastic Neural Networks with Mixed Delays Journal of Applied Mathematics |
| title | State Estimation for Discrete-Time Stochastic Neural Networks with Mixed Delays |
| title_full | State Estimation for Discrete-Time Stochastic Neural Networks with Mixed Delays |
| title_fullStr | State Estimation for Discrete-Time Stochastic Neural Networks with Mixed Delays |
| title_full_unstemmed | State Estimation for Discrete-Time Stochastic Neural Networks with Mixed Delays |
| title_short | State Estimation for Discrete-Time Stochastic Neural Networks with Mixed Delays |
| title_sort | state estimation for discrete time stochastic neural networks with mixed delays |
| url | http://dx.doi.org/10.1155/2014/209486 |
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