LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays
Discrete neural models are of great importance in numerical simulations and practical implementations. In the current paper, a discrete model of continuous-time neural networks with variable and distributed delays is investigated. By Lyapunov stability theory and techniques such as linear matrix ine...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/2013/732406 |
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| _version_ | 1832560838199738368 |
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| author | Hui Xu Ranchao Wu |
| author_facet | Hui Xu Ranchao Wu |
| author_sort | Hui Xu |
| collection | DOAJ |
| description | Discrete neural models are of great importance in numerical simulations and practical implementations. In the current paper, a discrete model of continuous-time neural networks with variable and distributed delays is investigated. By Lyapunov stability theory and techniques such as linear matrix inequalities, sufficient conditions guaranteeing the existence and global exponential stability of the unique equilibrium point are obtained. Introduction of LMIs enables one to take into consideration the sign of connection weights. To show the effectiveness of the method, an illustrative example, along with numerical simulation, is presented. |
| format | Article |
| id | doaj-art-e263b0eeeb364539be7e3168aee9ee24 |
| institution | Kabale University |
| issn | 1687-9120 1687-9139 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Mathematical Physics |
| spelling | doaj-art-e263b0eeeb364539be7e3168aee9ee242025-02-03T01:26:43ZengWileyAdvances in Mathematical Physics1687-91201687-91392013-01-01201310.1155/2013/732406732406LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple DelaysHui Xu0Ranchao Wu1School of Mathematics, Anhui University, Hefei 230039, ChinaSchool of Mathematics, Anhui University, Hefei 230039, ChinaDiscrete neural models are of great importance in numerical simulations and practical implementations. In the current paper, a discrete model of continuous-time neural networks with variable and distributed delays is investigated. By Lyapunov stability theory and techniques such as linear matrix inequalities, sufficient conditions guaranteeing the existence and global exponential stability of the unique equilibrium point are obtained. Introduction of LMIs enables one to take into consideration the sign of connection weights. To show the effectiveness of the method, an illustrative example, along with numerical simulation, is presented.http://dx.doi.org/10.1155/2013/732406 |
| spellingShingle | Hui Xu Ranchao Wu LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays Advances in Mathematical Physics |
| title | LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays |
| title_full | LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays |
| title_fullStr | LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays |
| title_full_unstemmed | LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays |
| title_short | LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays |
| title_sort | lmi based stability criteria for discrete time neural networks with multiple delays |
| url | http://dx.doi.org/10.1155/2013/732406 |
| work_keys_str_mv | AT huixu lmibasedstabilitycriteriafordiscretetimeneuralnetworkswithmultipledelays AT ranchaowu lmibasedstabilitycriteriafordiscretetimeneuralnetworkswithmultipledelays |