Abstract
In this paper, the fixed-time synchronization of stochastic impulsive neural networks with time-varying delays is studied. For the stability problem of nonlinear systems with impulsive effects, a new fixed-time stability theorem is proposed. Compared with other fixed-time stability theorems, it has better generality. Then, in order to realize fixed-time synchronization, a state feedback controller and an adaptive controller are designed respectively. Moreover, based on the new theorem, sufficient conditions for fixed-time synchronization of stochastic impulsive neural networks with time-varying delays are given. Finally, two simulation examples are given to verify the effectiveness of the theoretical results.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China (Nos. 62103165, 62101213 and 12026211), Shandong Provincial Natural Science Foundation (No. ZR2022ZD01), Shandong Provincial Higher Educational Youth Innovation Science and Technology Program (No. 2019KJN029), and Development Program Project of Youth Innovation Team of Institutions of Higher Learning in Shandong Province.
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Wang, Q., Zhao, H., Liu, A. et al. An Improved Fixed-Time Stability Theorem and its Application to the Synchronization of Stochastic Impulsive Neural Networks. Neural Process Lett 55, 7447–7467 (2023). https://doi.org/10.1007/s11063-023-11268-3
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DOI: https://doi.org/10.1007/s11063-023-11268-3