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New Criteria on Exponential Lag Synchronization of Switched Neural Networks with Time-Varying Delays

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Abstract

This paper addresses the problem of global exponential lag synchronization of switched neural networks with time-varying delays and general activation functions. Based on the Lyapunov–Krasovskii functional method and free weighting matrix technique, delay-dependent criteria for the global exponential lag synchronization of switched neural networks are derived in form of linear matrix inequalities. A numerical example is utilized to illustrate the characteristics of the results.

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Author information

Authors and Affiliations

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

    Yuting Cao & Shiping Wen

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

    Yuting Cao & Shiping Wen

  3. College of Science, Engineering and Technology at Hamad bin Khalifa University, Doha, 23874, Qatar

    Yuting Cao & Shiping Wen

  4. Texas A&M University at Qatar, 23874, Doha, Qatar

    Tingwen Huang

Authors
  1. Yuting Cao
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  2. Shiping Wen
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  3. Tingwen Huang
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Corresponding author

Correspondence to Shiping Wen.

Additional information

This work was supported by the Natural Science Foundation of China under Grants 61673187, 61403152, 61402218, and 61673188.

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Cao, Y., Wen, S. & Huang, T. New Criteria on Exponential Lag Synchronization of Switched Neural Networks with Time-Varying Delays. Neural Process Lett 46, 451–466 (2017). https://doi.org/10.1007/s11063-017-9599-1

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  • DOI: https://doi.org/10.1007/s11063-017-9599-1

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