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Pseudo Almost Periodic Solutions for Fuzzy Cellular Neural Networks with Multi-proportional Delays

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Abstract

This paper deals with a class of fuzzy cellular neural networks with multi-proportional delays. By applying the contraction mapping fixed point theorem and differential inequality techniques, a set of easily verifiable sufficient conditions are established for the existence and global attractivity of a unique pseudo almost periodic solution for the model, which improve and supplement previously known researches. Moreover, a numerical example is given to illustrate the feasibility and application of the obtained results.

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Acknowledgements

The authors would like to thank the anonymous referees and the editor for very helpful suggestions and comments which led to improvements of our original paper. This work was supported by the Natural Scientific Research Fund of Zhejiang Province of China (Grant Nos. LY16A010018, LY18A010019).

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Authors and Affiliations

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

    Jiaxin Liang, Hao Qian & Bingwen Liu

Authors
  1. Jiaxin Liang
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  2. Hao Qian
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  3. Bingwen Liu
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Corresponding author

Correspondence to Bingwen Liu.

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Liang, J., Qian, H. & Liu, B. Pseudo Almost Periodic Solutions for Fuzzy Cellular Neural Networks with Multi-proportional Delays. Neural Process Lett 48, 1201–1212 (2018). https://doi.org/10.1007/s11063-017-9774-4

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  • DOI: https://doi.org/10.1007/s11063-017-9774-4

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