Publication: Exponential dissipativity criteria for generalized BAM neural networks with variable delays
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Issued Date
2017-11-11
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09410643
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2-s2.0-85033467531
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Mahidol University
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SCOPUS
Bibliographic Citation
Neural Computing and Applications. (2017), 1-10
Suggested Citation
R. Saravanakumar, Grienggrai Rajchakit, M. Syed Ali, Young Hoon Joo Exponential dissipativity criteria for generalized BAM neural networks with variable delays. Neural Computing and Applications. (2017), 1-10. doi:10.1007/s00521-017-3224-0 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/42297
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Title
Exponential dissipativity criteria for generalized BAM neural networks with variable delays
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Abstract
© 2017 The Natural Computing Applications Forum This article evaluates the exponential dissipativity and passivity criterions for generalized bidirectional associative memory neural networks (BAMGNNs) including interval time-varying delayed signals. Exponential dissipativity and passivity criterions are proposed by making suitable Lyapunov–Krasovskii functional and proposing a novel approach. The improved reciprocally convex combination and weighted integral inequality techniques are utilized to obtain new exponential dissipativity and passivity conditions of such delayed BAMGNNs. The feasibility of the obtained results is clearly demonstrated by numerical examples.