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Exponential Stability of Pseudo Almost Periodic Solutions for Cellular Neural Networks with Multi-Proportional Delays

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Abstract

This paper concerns with the pseudo almost periodic solutions for a class of cellular neural networks model with multi-proportional delays. By applying contraction mapping fixed point theorem and differential inequality techniques, we establish some sufficient conditions for the existence and exponential stability of pseudo almost periodic solutions for the model, which improve and supplement existing ones. Moreover, an example and its numerical simulation are given to support the theoretical results.

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Acknowledgments

The author would like to express the sincere appreciation to the reviewers for their helpful comments in improving the presentation and quality of the paper. This work was supported by the Natural Scientific Research Fund of Hunan Provincial of China (Grant Nos. 2016JJ6103, 2016JJ6104), and the Construction Program of the Key Discipline in Hunan University of Arts and Science-Applied Mathematics.

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  1. College of Mathematics and Computer Science, Hunan University of Arts and Science, Changde, 415000, Hunan, People’s Republic of China

    Yuehua Yu

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  1. Yuehua Yu
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Correspondence to Yuehua Yu.

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Yu, Y. Exponential Stability of Pseudo Almost Periodic Solutions for Cellular Neural Networks with Multi-Proportional Delays. Neural Process Lett 45, 141–151 (2017). https://doi.org/10.1007/s11063-016-9516-z

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  • DOI: https://doi.org/10.1007/s11063-016-9516-z

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