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Proceedings of the 2015 Chinese Intelligent Automation Conference pp 21–28Cite as

Adaptive Cluster Synchronization for Weighted Cellular Neural Networks with Time-Varying Delays

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 338))

Abstract

In this paper, the adaptive cluster synchronization for weighted cellular neural networks with multiple time-varying delays is investigated. The weighted configuration matrix in the networks under consideration is time-varying, which does not need to satisfy the diffusive coupling conditions or be symmetric. Based on Lyapunov stability theory, Kronecker product, and adaptive control method an adaptive strategy is derived to ensure each node in the networks achieves the asymptotical cluster mean square synchronization. The numerical simulations are performed to verify the effectiveness of the theoretical results.

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Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Jiangsu University, Zhenjiang, 212013, China

    Yuxiu Li

  2. Nonlinear Scientific Research Center, Jiangsu University, Zhenjiang, 212013, China

    Guoliang Cai

Authors
  1. Yuxiu Li
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  2. Guoliang Cai
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Corresponding author

Correspondence to Yuxiu Li .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Zhidong Deng

  2. Department of Computer Science and Techn, Tsinghua University, Beijing, China

    Hongbo Li

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Li, Y., Cai, G. (2015). Adaptive Cluster Synchronization for Weighted Cellular Neural Networks with Time-Varying Delays. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46466-3_3

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  • DOI: https://doi.org/10.1007/978-3-662-46466-3_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46465-6

  • Online ISBN: 978-3-662-46466-3

  • eBook Packages: EngineeringEngineering (R0)

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