Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays
Employing fixed point theorem, we make a further investigation of a class of neural networks with delays in this paper. A family of sufficient conditions is given for checking global exponential stability. These results have important leading significance in the design and applications of globally s...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2009-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2009/415786 |
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| _version_ | 1832567968840548352 |
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| author | Yingxin Guo Mingzhi Xue |
| author_facet | Yingxin Guo Mingzhi Xue |
| author_sort | Yingxin Guo |
| collection | DOAJ |
| description | Employing fixed point theorem, we make a further investigation of a class of
neural networks with delays in this paper. A family of sufficient conditions is given for
checking global exponential stability. These results have important leading significance in
the design and applications of globally stable neural networks with delays. Our results
extend and improve some earlier publications. |
| format | Article |
| id | doaj-art-d5d16f9349844a5694d82c065d59b1cf |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2009-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-d5d16f9349844a5694d82c065d59b1cf2025-02-03T01:00:02ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2009-01-01200910.1155/2009/415786415786Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying DelaysYingxin Guo0Mingzhi Xue1Department of Mathematics, Qufu Normal University, Qufu 273165, Shandong, ChinaDepartment of Mathematics, Shangqiu Normal University, Shangqiu 476000, Henan, ChinaEmploying fixed point theorem, we make a further investigation of a class of neural networks with delays in this paper. A family of sufficient conditions is given for checking global exponential stability. These results have important leading significance in the design and applications of globally stable neural networks with delays. Our results extend and improve some earlier publications.http://dx.doi.org/10.1155/2009/415786 |
| spellingShingle | Yingxin Guo Mingzhi Xue Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays Discrete Dynamics in Nature and Society |
| title | Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays |
| title_full | Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays |
| title_fullStr | Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays |
| title_full_unstemmed | Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays |
| title_short | Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays |
| title_sort | periodic solutions and exponential stability of a class of neural networks with time varying delays |
| url | http://dx.doi.org/10.1155/2009/415786 |
| work_keys_str_mv | AT yingxinguo periodicsolutionsandexponentialstabilityofaclassofneuralnetworkswithtimevaryingdelays AT mingzhixue periodicsolutionsandexponentialstabilityofaclassofneuralnetworkswithtimevaryingdelays |