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Global Convergence on Asymptotically Almost Periodic SICNNs with Nonlinear Decay Functions

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Abstract

In this paper, we propose a class of asymptotically almost periodic shunting inhibitory cellular neural networks with mixed delays and nonlinear decay functions. Without using the exponential dichotomy theory of linear differential equations, a set of easily verifiable sufficient conditions are established to show that every solution of the considered system is asymptotically almost periodic, and converges to a same almost periodic function as \(t\rightarrow +\infty \), which improve and supplement some previously known researches. Finally, a numerical example is given to demonstrate the effectiveness of the obtained results.

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Acknowledgements

Our deepest gratitude goes to the anonymous reviewers for their careful work and thoughtful suggestions that have helped improve this paper substantially. This work was supported by Natural Scientific Research Fund of Zhejiang Province of China (Grant No. LY18A010019), Natural Scientific Research Fund of Hunan Provincial of China (Grant Nos. (2016JJ1001, 2016JJ6103, 2016JJ6104) and Natural Scientific Research Fund of Hunan Provincial Education Department of China (Grant No. 17C1076).

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Authors and Affiliations

  1. School of Mathematics and Statistics, Changsha University of Science and Technology, Changsha, 410114, Hunan, People’s Republic of China

    Chuangxia Huang, Xuemei Tian & Luanshan Yang

  2. College of Mathematics, Physics and Information Engineering, Jiaxing University, Jiaxing, 314001, Zhejiang, People’s Republic of China

    Bingwen Liu & Xiaoxiao Zhang

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  1. Chuangxia Huang
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  2. Bingwen Liu
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  3. Xuemei Tian
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  4. Luanshan Yang
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  5. Xiaoxiao Zhang
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Correspondence to Bingwen Liu.

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Huang, C., Liu, B., Tian, X. et al. Global Convergence on Asymptotically Almost Periodic SICNNs with Nonlinear Decay Functions. Neural Process Lett 49, 625–641 (2019). https://doi.org/10.1007/s11063-018-9835-3

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