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\(H_{\infty }\) filter design for delayed static neural networks with Markovian switching and randomly occurred nonlinearity

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Abstract

The paper is concerned with the problem of \(H_{\infty }\) filter design for delayed static neural networks with Markovian switching and randomly occurred nonlinearity. The random phenomenon is described in terms of a Bernoulli stochastic variable. Based on the reciprocally convex approach, a lower bound lemma is proposed to handle the double- and triple-integral terms in the time derivative of the Lyapunov function. Finally, the optimal performance index is obtained via solving linear matrix inequalities(LMIs). The result is not only less conservative but the time derivative of the time delay can be greater than one. Numerical examples with simulation results are provided to illustrate the effectiveness of the developed results.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grants 11301004, 61403002, 61503121, the Natural Science Foundation of Jiangsu Province under Grant BK20130239, the Research Fund for the Doctoral Program of Higher Education of China under Grant 20130094120015, and the Fundamental Research Funds for the Central Universities under Grant 2016B07314.

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Authors and Affiliations

  1. College of Internet of Things Engineering, Hohai University, Changzhou, 213022, China

    Yaling Cheng, Mingang Hua & Juntao Fei

  2. School of Mathematical Sciences, Anhui University, Hefei, 230601, China

    Pei Cheng

  3. School of Electrical and Information Engineering, Anhui University of Technology, Maanshan, 243000, China

    Fengqi Yao

Authors
  1. Yaling Cheng
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  2. Mingang Hua
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  3. Pei Cheng
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Correspondence to Mingang Hua.

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Cheng, Y., Hua, M., Cheng, P. et al. \(H_{\infty }\) filter design for delayed static neural networks with Markovian switching and randomly occurred nonlinearity. Int. J. Mach. Learn. & Cyber. 9, 903–915 (2018). https://doi.org/10.1007/s13042-016-0613-0

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  • DOI: https://doi.org/10.1007/s13042-016-0613-0

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