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Robust Exponential Stabilization for Switched Neutral Neural Networks with Mixed Time-Varying Delays

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Abstract

This paper studies the problems of exponential stabilization for a class of uncertain switched neutral neural networks with mixed time-varying delays. Based on the multiple Lyapunov-like functional method and the average dwell time method, the sufficient conditions which guarantee exponential stabilization of the uncertain switched neutral neural networks with mixed time-varying delays are presented. Averaged well time of switching signals is also given. Moreover, a design scheme for the stabilizing feedback controllers is proposed to guarantee exponential stability of corresponding closed-loop systems. Finally, two examples are given to illustrate the applicability and the effectiveness of the proposed method.

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Acknowledgements

This work is supported by the Natural Science Foundation of China under Grants 61703307 and 61603272.

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Correspondence to Yali Dong.

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Dong, Y., Guo, L., Hao, J. et al. Robust Exponential Stabilization for Switched Neutral Neural Networks with Mixed Time-Varying Delays. Neural Process Lett 50, 1381–1400 (2019). https://doi.org/10.1007/s11063-018-9928-z

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