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Adaptive Exponential State Estimation for Markovian Jumping Neural Networks with Multi-delays and Lévy Noises

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Abstract

This paper discusses the adaptive exponential state estimation problem of neutral-type neural networks with multi-delays and Lévy noises. The M-matrix method being different from other methods, such as the LMIs method, has been applied to deal with the problem. According to the M-matrix method, some state estimation criteria for neural networks concerning neutral-type delays and no neutral-type delays are acquired to ensure the adaptive exponential estimation. Finally, a simulation example is offered to show the advantages of the theoretical results.

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Acknowledgements

This study was funded by the National Natural Science Foundation of China (61673257; 11501367; 61573095; 61673221); the Natural Science Foundation of Jiangsu Province (BK20181418); the fifteenth batch of Six Talent Peaks Project in Jiangsu Province (DZXX-019).

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Authors and Affiliations

  1. School of Statistics and Mathematics, Shanghai Lixin University of Accounting and Finance, Shanghai, 201620, China

    Qiaoyu Chen

  2. School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China

    Dongbing Tong

  3. College of Information Sciences and Technology, Donghua University, Shanghai, 200051, China

    Wuneng Zhou

  4. School of Finance, Nanjing Audit University, Jiangsu, 211815, China

    Yuhua Xu

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  1. Qiaoyu Chen
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  2. Dongbing Tong
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  3. Wuneng Zhou
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  4. Yuhua Xu
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Correspondence to Dongbing Tong, Wuneng Zhou or Yuhua Xu.

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Chen, Q., Tong, D., Zhou, W. et al. Adaptive Exponential State Estimation for Markovian Jumping Neural Networks with Multi-delays and Lévy Noises. Circuits Syst Signal Process 38, 3321–3339 (2019). https://doi.org/10.1007/s00034-018-1004-4

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  • DOI: https://doi.org/10.1007/s00034-018-1004-4

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