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Passivity analysis of uncertain neural networks with mixed time-varying delays

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Abstract

This paper addresses the passivity problem for uncertain neural networks with both discrete and distributed time-varying delays. It is assumed that the parameter uncertainties are norm-bounded. By construction of an augmented Lyapunov–Krasovskii functional and utilization of zero equalities, improved passivity criteria for the networks are derived in terms of linear matrix inequalities (LMIs) via new approaches. Through three numerical examples, the effectiveness to enhance the feasible region of the proposed criteria is demonstrated.

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Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (2012-0000479), and by a grant of the Korea Healthcare Technology R & D Project, Ministry of Health & Welfare, Republic of Korea (A100054).

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Authors and Affiliations

  1. School of Electrical Engineering, Chungbuk National University, 52 Naesudong-ro, Heungduk-gu, Cheongju, 361-763, Republic of Korea

    O. M. Kwon & M. J. Park

  2. Department of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Kyongsan, 712-749, Republic of Korea

    Ju H. Park

  3. School of Electronic Engineering, Daegu University, Gyungsan, 712-714, Republic of Korea

    S. M. Lee

  4. Department of Biomedical Engineering, School of Medicine, Chungbuk National University, 52 Naesudong-ro, Heungduk-gu, Cheongju, 361-763, Republic of Korea

    E. J. Cha

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  1. O. M. Kwon
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  2. M. J. Park
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  3. Ju H. Park
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Correspondence to Ju H. Park.

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Kwon, O.M., Park, M.J., Park, J.H. et al. Passivity analysis of uncertain neural networks with mixed time-varying delays. Nonlinear Dyn 73, 2175–2189 (2013). https://doi.org/10.1007/s11071-013-0932-6

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