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Global Stabilization for Delayed Fuzzy Inertial Neural Networks

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Advances in Neural Networks – ISNN 2019 (ISNN 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11555))

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Abstract

This paper studies the global stabilization problem for a class of fuzzy inertial neural networks (FINN) with time delays and deals with the FINN directly by non-reduced order method. By Lyapunov theory and some analytical techniques, some criteria of global asymptotic and exponential stabilization for the considered FINN are obtained. An example is given to show the effectiveness and validity of the theoretical results.

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Author information

Authors and Affiliations

  1. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, 430074, China

    Qiang Xiao & Zhigang Zeng

  2. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan, 430074, China

    Qiang Xiao & Zhigang Zeng

  3. Department of Mathematics, Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

Authors
  1. Qiang Xiao
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  2. Tingwen Huang
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  3. Zhigang Zeng
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Corresponding author

Correspondence to Zhigang Zeng .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Huchuan Lu

  2. Sichuan University, Chengdu, China

    Huajin Tang

  3. Northeastern University, Shenyang, China

    Zhanshan Wang

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Xiao, Q., Huang, T., Zeng, Z. (2019). Global Stabilization for Delayed Fuzzy Inertial Neural Networks. In: Lu, H., Tang, H., Wang, Z. (eds) Advances in Neural Networks – ISNN 2019. ISNN 2019. Lecture Notes in Computer Science(), vol 11555. Springer, Cham. https://doi.org/10.1007/978-3-030-22808-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-22808-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22807-1

  • Online ISBN: 978-3-030-22808-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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