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Robust Stability of Inertial BAM Neural Networks with Time Delays and Uncertainties via Impulsive Effect

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Abstract

This paper investigates the robust stability of inertial bidirectional association memory (BAM) neural networks with time delays and uncertainties via impulsive control. Firstly, utilizing suitable variable substitution, the seconded-order inertial BAM neural networks can be transformed into first-order differential equations. Secondly, Under the framework of Lyapunov stability method, Halanay inequality and impulsive differential inequations, we develop some techniques of impulsive to achieve the robust stability of inertial BAM neural networks. These obtained criteria are capable of reducing computational burden in the theoretical part. Some effective sufficient conditions are established for the realization of stability of the underlying network. Finally, an illustrative example is given to verify the validity of the obtained results.

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Acknowledgements

This work is supported by Fundamental Research Funds for the Central Universities (Grant Nos. XDJK2016BC137, SWU116004), Natural Science Foundation of China (Grant Nos. 61374078, 61403313, 61633011). This publication was made possible by NPRP Grant # NPRP 7-1482-1-278 from the Qatar National Research Fund (a member of Qatar Foundation).

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Correspondence to Tingwen Huang.

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Zhang, W., Huang, T., Li, C. et al. Robust Stability of Inertial BAM Neural Networks with Time Delays and Uncertainties via Impulsive Effect. Neural Process Lett 48, 245–256 (2018). https://doi.org/10.1007/s11063-017-9713-4

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  • DOI: https://doi.org/10.1007/s11063-017-9713-4

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