Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays
A class of interval neural networks with time-varying delays and distributed delays is investigated. By employing H-matrix and M-matrix theory, homeomorphism techniques, Lyapunov functional method, and linear matrix inequality approach, sufficient conditions for the existence, uniqueness, and global...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2012/647231 |
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| _version_ | 1832567627229167616 |
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| author | Yanke Du Rui Xu |
| author_facet | Yanke Du Rui Xu |
| author_sort | Yanke Du |
| collection | DOAJ |
| description | A class of interval neural networks with time-varying delays and distributed delays is investigated. By employing H-matrix and M-matrix theory, homeomorphism techniques, Lyapunov functional method, and linear matrix inequality approach, sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point to the neural networks are established and some previously published results are improved and generalized. Finally, some numerical examples are given to illustrate the effectiveness of the theoretical results. |
| format | Article |
| id | doaj-art-f0161d03c91043cdae93aa9e67db0bbe |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-f0161d03c91043cdae93aa9e67db0bbe2025-02-03T01:01:06ZengWileyAbstract and Applied Analysis1085-33751687-04092012-01-01201210.1155/2012/647231647231Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed DelaysYanke Du0Rui Xu1Institute of Applied Mathematics, Shijiazhuang Mechanical Engineering College, Shijiazhuang 050003, ChinaInstitute of Applied Mathematics, Shijiazhuang Mechanical Engineering College, Shijiazhuang 050003, ChinaA class of interval neural networks with time-varying delays and distributed delays is investigated. By employing H-matrix and M-matrix theory, homeomorphism techniques, Lyapunov functional method, and linear matrix inequality approach, sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point to the neural networks are established and some previously published results are improved and generalized. Finally, some numerical examples are given to illustrate the effectiveness of the theoretical results.http://dx.doi.org/10.1155/2012/647231 |
| spellingShingle | Yanke Du Rui Xu Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays Abstract and Applied Analysis |
| title | Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays |
| title_full | Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays |
| title_fullStr | Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays |
| title_full_unstemmed | Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays |
| title_short | Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays |
| title_sort | global robust exponential stability analysis for interval neural networks with mixed delays |
| url | http://dx.doi.org/10.1155/2012/647231 |
| work_keys_str_mv | AT yankedu globalrobustexponentialstabilityanalysisforintervalneuralnetworkswithmixeddelays AT ruixu globalrobustexponentialstabilityanalysisforintervalneuralnetworkswithmixeddelays |