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A Delay-Dependent Approach to Passivity Analysis for Uncertain Neural Networks with Time-varying Delay

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Abstract

This paper deals with the problem of passivity analysis for neural networks with time-varying delay, which is subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. Delay-dependent passivity condition is proposed by using the free-weighting matrix approach. These passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by using standard algorithms. Two illustrative examples are provided to demonstrate the effectiveness of the proposed criteria.

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Authors and Affiliations

  1. Department of Industrial Education and Technology, National Changhua University of Education, Changhua, 500, Taiwan, ROC

    Chien-Yu Lu & Chin-Wen Liao

  2. Department of Biomechatronics Engineering, National Pingtung University of Science & Technology, Pingtung, 912, Taiwan, ROC

    Hsun-Heng Tsai

  3. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, 807, Taiwan, ROC

    Te-Jen Su

  4. Department of Electrical Engineering, National Cheng-Kung University, Tainan City, 701, Taiwan, ROC

    Jason Sheng-Hong Tsai

Authors
  1. Chien-Yu Lu
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  2. Hsun-Heng Tsai
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  3. Te-Jen Su
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  4. Jason Sheng-Hong Tsai
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  5. Chin-Wen Liao
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Corresponding author

Correspondence to Chien-Yu Lu.

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Lu, CY., Tsai, HH., Su, TJ. et al. A Delay-Dependent Approach to Passivity Analysis for Uncertain Neural Networks with Time-varying Delay. Neural Process Lett 27, 237–246 (2008). https://doi.org/10.1007/s11063-008-9072-2

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  • DOI: https://doi.org/10.1007/s11063-008-9072-2

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