LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays
This paper studies the problems of global exponential robust stability of high-order hopfield neural networks with time-varying delays. By employing a new Lyapunov-Krasovskii functional and linear matrix inequality, some criteria of global exponential robust stability for the high-order neural netwo...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2012/182745 |
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| _version_ | 1850166586770456576 |
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| author | Yangfan Wang Linshan Wang |
| author_facet | Yangfan Wang Linshan Wang |
| author_sort | Yangfan Wang |
| collection | DOAJ |
| description | This paper studies the problems of global exponential robust stability of high-order hopfield neural networks with time-varying delays. By employing a new Lyapunov-Krasovskii functional and linear matrix inequality, some criteria of global exponential robust stability for the high-order neural networks are established, which are easily verifiable and have a wider adaptive. |
| format | Article |
| id | doaj-art-e3efc09ce64f40e4905b9736b68ab591 |
| institution | OA Journals |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-e3efc09ce64f40e4905b9736b68ab5912025-08-20T02:21:24ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/182745182745LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying DelaysYangfan Wang0Linshan Wang1College of Marine Life Science, Ocean University of China, Qingdao 266071, ChinaDepartment of Mathematics, Ocean University of China, Qingdao 266071, ChinaThis paper studies the problems of global exponential robust stability of high-order hopfield neural networks with time-varying delays. By employing a new Lyapunov-Krasovskii functional and linear matrix inequality, some criteria of global exponential robust stability for the high-order neural networks are established, which are easily verifiable and have a wider adaptive.http://dx.doi.org/10.1155/2012/182745 |
| spellingShingle | Yangfan Wang Linshan Wang LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays Journal of Applied Mathematics |
| title | LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays |
| title_full | LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays |
| title_fullStr | LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays |
| title_full_unstemmed | LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays |
| title_short | LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays |
| title_sort | lmi based approach for exponential robust stability of high order hopfield neural networks with time varying delays |
| url | http://dx.doi.org/10.1155/2012/182745 |
| work_keys_str_mv | AT yangfanwang lmibasedapproachforexponentialrobuststabilityofhighorderhopfieldneuralnetworkswithtimevaryingdelays AT linshanwang lmibasedapproachforexponentialrobuststabilityofhighorderhopfieldneuralnetworkswithtimevaryingdelays |