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Exponential Lag Synchronization and Global Dissipativity for Delayed Fuzzy Cohen–Grossberg Neural Networks with Discontinuous Activations

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Abstract

This paper investigates the qualitative behavior of a new class of fuzzy Cohen–Grossberg neural networks with discontinuous neuron activations and mixed delays. Roughly speaking, some novel sufficient conditions are established in order to demonstrate the global dissipativity and the exponential lag synchronization of the considered model by using the theory of Filippov systems and Lyapunov method. Finally, two examples are presented to show the effectiveness of the obtained results.

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Acknowledgements

The authors would like to thank the anonymous reviewers and the editor for their constructive comments, which greatly improved the quality of this paper.

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Authors and Affiliations

  1. University of Sousse, École Supérieure des Sciences et de Technologie de Hammam-Sousse, Laboratory of Mathematical Physic, Specials Functions and Applications LR11ES35, 4011, Hammam-Sousse, Tunisia

    Meryem Abdelaziz

  2. University of Sousse, Department of Computer Science ISSATS, École Supérieure des Sciences et de Technologie, Laboratory of Math Physics, Specials Functions and Applications LR11ES35, 4002, Sousse, Tunisia

    Farouk Chérif

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  1. Meryem Abdelaziz
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Correspondence to Meryem Abdelaziz.

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Abdelaziz, M., Chérif, F. Exponential Lag Synchronization and Global Dissipativity for Delayed Fuzzy Cohen–Grossberg Neural Networks with Discontinuous Activations. Neural Process Lett 51, 1653–1676 (2020). https://doi.org/10.1007/s11063-019-10169-8

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