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Stability of Complex-Valued Neural Networks with Two Additive Time-Varying Delay Components

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Advances in Neural Networks - ISNN 2017 (ISNN 2017)

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Abstract

In this paper, a class of complex-valued neural networks including two additive time-varying delay components has been discussed. By making use of the combinational Lyapunov-Krasovskii functional and free weighting matrix method, as well as matrix inequality technique, a delay-dependent criterion of stability is derived.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grants 61473332, 11402214, and 61673169 and the Program of Chongqing Innovation Team Project in University under Grant CXTDX201601022.

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Authors and Affiliations

  1. College of Science, Huzhou University, Huzhou, 313000, China

    Zhenjiang Zhao

  2. Department of Mathematics, Chongqing Jiaotong University, Chongqing, 400074, China

    Qiankun Song

  3. Deloitte Consulting (Shanghai) Co. Ltd., Shanghai, 200002, China

    Yuchen Zhao

Authors
  1. Zhenjiang Zhao
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  2. Qiankun Song
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  3. Yuchen Zhao
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Corresponding authors

Correspondence to Zhenjiang Zhao , Qiankun Song or Yuchen Zhao .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Fengyu Cong

  2. City University of Hong Kong, Kowloon Tong, Hong Kong

    Andrew Leung

  3. Chinese Academy of Sciences, Beijing, China

    Qinglai Wei

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Zhao, Z., Song, Q., Zhao, Y. (2017). Stability of Complex-Valued Neural Networks with Two Additive Time-Varying Delay Components. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10261. Springer, Cham. https://doi.org/10.1007/978-3-319-59072-1_66

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  • DOI: https://doi.org/10.1007/978-3-319-59072-1_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59071-4

  • Online ISBN: 978-3-319-59072-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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