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Adaptive Finite-Time Complete Periodic Synchronization of Memristive Neural Networks with Time Delays

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Abstract

This paper is concerned with the adaptive finite-time complete periodic synchronization issue for memristive based neural networks with time delays. Under the framework of Filippov solutions of the differential equations with discontinuous right-hand side, based on Mawhin-like coincidence theorem in set-valued analysis theory, the existence of periodic solution is proved. By applying Lyapunov–Krasovskii functional approach, adaptive controller is designed and unknown control parameters are determined by adaptive update law. A novel and useful finite-time complete synchronization condition is obtained in terms of linear matrix inequalities to ensure the synchronization goal. An illustrative example is given to demonstrate the effectiveness of the theoretical results.

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Acknowledgments

The authors are extremely grateful to the Editors and anonymous reviewers for their valuable comments and constructive suggestions, which help to enrich the content and improve the presentation of this paper.

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Authors and Affiliations

  1. Department of Applied Mathematics, Yanshan University, Qinhuangdao, 066001, China

    Huaiqin Wu, Ruoxia Li, Xiaowei Zhang & Rong Yao

Authors
  1. Huaiqin Wu
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  2. Ruoxia Li
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  3. Xiaowei Zhang
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  4. Rong Yao
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Correspondence to Huaiqin Wu.

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Wu, H., Li, R., Zhang, X. et al. Adaptive Finite-Time Complete Periodic Synchronization of Memristive Neural Networks with Time Delays. Neural Process Lett 42, 563–583 (2015). https://doi.org/10.1007/s11063-014-9373-6

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  • DOI: https://doi.org/10.1007/s11063-014-9373-6

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