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Synchronization Control of Coupled Memristor-Based Neural Networks with Mixed Delays and Stochastic Perturbations

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Abstract

This paper investigates the synchronization control problem of coupled memristor-based neural networks (CMNNs) with mixed delays and stochastic perturbations. By utilizing simple feedback controllers, some novel sufficient conditions are derived to ensure the exponential synchronization of CMNNs with mixed delays and stochastic perturbations in mean square. In addition, by means of adaptive feedback controllers, the asymptotic synchronization of CMNNs with mixed delays and stochastic perturbations in mean square can also be achieved via stochastic LaSalle invariance principle. Numerical simulations are presented to illustrate the effectiveness of the theoretical results.

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Acknowledgements

The work is supported by the National Key Research and Development Program (Grant Nos. 2016YFB0800602 and 2016YFB0800604), and the National Natural Science Foundation of China (Grant Nos. 61573067 and 61472045).

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Authors and Affiliations

  1. Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Chuan Chen, Lixiang Li, Haipeng Peng & Yixian Yang

  2. State Key Laboratory of Public Big Data, 550025, Guizhou, China

    Yixian Yang

  3. College of Computer Science, Sichuan University, Sichuan, 610065, China

    Tao Li

Authors
  1. Chuan Chen
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  2. Lixiang Li
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  3. Haipeng Peng
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  4. Yixian Yang
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  5. Tao Li
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Correspondence to Lixiang Li.

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Chen, C., Li, L., Peng, H. et al. Synchronization Control of Coupled Memristor-Based Neural Networks with Mixed Delays and Stochastic Perturbations. Neural Process Lett 47, 679–696 (2018). https://doi.org/10.1007/s11063-017-9675-6

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