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New results on almost periodic solutions for CNNs with time-varying leakage delays

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Abstract

In this paper, based on the exponential dichotomy theory and contraction mapping fixed point theorem, we obtain some sufficient conditions ensuring the global exponential stability of almost periodic solutions for a new generalized cellular neural network model with time-varying delays in leakage (or forgetting) terms. Our results complement some recent ones. Moreover, an illustrative example and its numerical simulation are given to demonstrate the effectiveness of the obtained results.

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Acknowledgments

The author would like to express the sincere appreciation to the editor and reviewers for their helpful comments in improving the presentation and quality of the paper. In particular, the authors express the sincere gratitude to Prof. Jianli Li for the helpful discussion when this revision work is carried out. This work was supported by the Construct Program of the Key Discipline in Hunan Province, the Science and Technology Planning project of Technology Department of Hunan Province (Grant No. 2012FJ4300), the National Natural Science Foundation of Hunan Province (Grant Nos. 13JJ3120, 14JJ2133) and the Natural Scientific Research Fund of Hunan Provincial Education Department of China (Grant No. 13C880).

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  1. Department of Mathematics, Xiangnan College, Chenzhou, 423000, Hunan, People’s Republic of China

    Yanli Xu

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  1. Yanli Xu
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Correspondence to Yanli Xu.

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Xu, Y. New results on almost periodic solutions for CNNs with time-varying leakage delays. Neural Comput & Applic 25, 1293–1302 (2014). https://doi.org/10.1007/s00521-014-1610-4

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  • DOI: https://doi.org/10.1007/s00521-014-1610-4

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