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Passivity analysis for uncertain discrete-time stochastic BAM neural networks with time-varying delays

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Abstract

This paper is concerned with the passivity analysis problem for a class of discrete-time stochastic bidirectional associative memory neural networks with time-varying delays. Furthermore, the results are extended to the robust passivity analysis with mixed time delays that consist of both the discrete and distributed time delays, and the uncertainties are assumed to be time-varying norm bounded parameter uncertainties. By constructing a new Lyapunov–Krasovskii functional and introducing some appropriate free-weighting matrices, a delay-dependent passivity criterion is derived in terms of LMIs whose feasibility can be easily checked by some available software packages. Finally, two numerical examples with simulation results are given to demonstrate the effectiveness and usefulness of the proposed results.

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Acknowledgements

The authors are very much thankful to the reviewers and editors for their valuable comments and suggestions for improving this work. The work of the corresponding author was supported by “UGC-BSR Start-Up Grant No.F.20-6(13)/2012(BSR).”

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Raja, R., Raja, U.K., Samidurai, R. et al. Passivity analysis for uncertain discrete-time stochastic BAM neural networks with time-varying delays. Neural Comput & Applic 25, 751–766 (2014). https://doi.org/10.1007/s00521-014-1545-9

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  • DOI: https://doi.org/10.1007/s00521-014-1545-9

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