A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay
This paper studies the problem for exponential stability of switched recurrent neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessarily differentiable. By constructing a set of argumented Lyapunov-Krasovskii function...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2014
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| Online Access: | http://www.scopus.com/inward/record.url?eid=2-s2.0-84878629570&partnerID=40&md5=176925f6afb29f71c0b5f31c4dd416a1 http://cmuir.cmu.ac.th/handle/6653943832/7237 |
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| Institution: | Chiang Mai University |
| Language: | English |
| Summary: | This paper studies the problem for exponential stability of switched recurrent neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessarily differentiable. By constructing a set of argumented Lyapunov-Krasovskii functionals combined with the Newton-Leibniz formula, a switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay is designed via linear matrix inequalities, and new sufficient conditions for the exponential stability of switched recurrent neural networks with interval time-varying delay via linear matrix inequalities (LMIs) are derived. A numerical example is given to illustrate the effectiveness of the obtained result. © 2013 Rajchakit et al.; licensee Springer. |
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