Exponential Stability of Periodic Solutions for Inertial Type BAM Cohen-Grossberg Neural Networks
The existence and exponential stability of periodic solutions for inertial type BAM Cohen-Grossberg neural networks are investigated. First, by properly choosing variable substitution, the system is transformed to first order differential equation. Second, some sufficient conditions that ensure the...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/857341 |
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| Summary: | The existence and exponential stability of periodic solutions for inertial type BAM Cohen-Grossberg neural
networks are investigated. First, by properly choosing variable substitution, the system is transformed to first order differential
equation. Second, some sufficient conditions that ensure the existence and exponential stability of periodic solutions for the system are obtained by constructing suitable Lyapunov functional and using differential mean value theorem and inequality technique. Finally, two examples are given to illustrate the effectiveness of the results. |
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| ISSN: | 1085-3375 1687-0409 |