Existence and exponential stability of periodic solution for fuzzy BAM neural networks with periodic coefficient
A class of fuzzy bidirectional associated memory (BAM) networks with periodic coefficients is studied. Some sufficient conditions are established for the existence and global exponential stability of a periodic solution of such fuzzy BAM neural networks by using a continuation theorem based on the...
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| Date: | 2011 |
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| Main Authors: | , , , , , |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Mathematics, NAS of Ukraine
2011
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| Online Access: | https://umj.imath.kiev.ua/index.php/umj/article/view/2833 |
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| Journal Title: | Ukrains’kyi Matematychnyi Zhurnal |
| Download file: |  |
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Ukrains’kyi Matematychnyi Zhurnal| Summary: | A class of fuzzy bidirectional associated memory (BAM) networks with periodic coefficients is studied.
Some sufficient conditions are established for the existence and global exponential stability of a periodic solution
of such fuzzy BAM neural networks by using a continuation theorem based on the coincidence degree and the Lyapunov-function method.
The sufficient conditions are easy to verify in pattern recognition and automatic control. Finally, an example is given to show the feasibility and efficiency of our results. |
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