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New sufficient conditions on global asymptotic synchronization of inertial delayed neural networks by using integrating inequality techniques

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Abstract

In this paper, the global asymptotic synchronization of a class of inertial delayed neural networks is investigated. Instead of using conventional study methods of global exponential/asymptotic synchronization: linear matrix inequality method, matrix measure strategy and stability theory methods, by using constructed integrating inequality and inequality techniques, we present two new sufficient conditions on global asymptotic synchronization for the drive-response inertial delayed neural networks under two new controllers by using different Lyapunov functions from those used in the existing papers. The presented results are more concise and easy to verify in practice than those obtained in existing papers. Hence, our results extend the study method of global synchronization for delayed neural networks.

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Authors and Affiliations

  1. College of Mathematics and Econometrics, Hunan University, Changsha, 410082, China

    Zhengqiu Zhang & Ling Ren

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  1. Zhengqiu Zhang
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  2. Ling Ren
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Correspondence to Zhengqiu Zhang.

Additional information

Project supported by the Innovation Platform Open Fund in Hunan Province Colleges and Universities of China (No: 201485).

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Zhang, Z., Ren, L. New sufficient conditions on global asymptotic synchronization of inertial delayed neural networks by using integrating inequality techniques. Nonlinear Dyn 95, 905–917 (2019). https://doi.org/10.1007/s11071-018-4603-5

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  • DOI: https://doi.org/10.1007/s11071-018-4603-5

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