Abstract
Based on the structure and the working mechanism of real neurons, a new mathematical model of the memristor-based switching networks (MSNs) with multiple links and time-varying delays is proposed. Further, we study the asymptotic and finite-time synchronizations of the proposed MSNs via adaptive controller and intermittent controller. Based on the stability theory and the linear matrix inequality theory, some effective asymptotic and finite-time synchronization criteria are derived to ensure the stability of the error system between the drive and response networks. Finally, numerical simulations show the effectiveness and the correctness of our results.
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Acknowledgements
The authors would like to thank all the editor, associate editor as well as the anonymous reviewers for their constructive suggestions and valuable comments, which are important and helpful to improve the quality of this paper. The work is supported by the National Key Research and Development Program (Grant No. 2016YFB0800602) and the National Natural Science Foundation of China (Grant Nos. 61472045, 61573067, 61771071).
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Qiu, B., Li, L., Peng, H. et al. Asymptotic and finite-time synchronization of memristor-based switching networks with multi-links and impulsive perturbation. Neural Comput & Applic 31, 4031–4047 (2019). https://doi.org/10.1007/s00521-017-3312-1
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DOI: https://doi.org/10.1007/s00521-017-3312-1