Finite-time anti-synchronisation of delayed Hopfield neural networks with discontinuous activations

ABSTRACT

This paper is concerned with the finite-time anti-synchronisation problem of delayed Hopfield neural networks with discontinuous activations. By introducing a novel analytical method, new synchronisation criteria are established without the help of nonsmooth finite-time convergence theorem. The designed controllers herein are independent of time delay, and the established criteria depending on the time delay and system parameters are very simple to implement in practice and avoid complex computation, the upper-bound of the settling time is explicitly estimated as well. The new findings in this paper provide a new viewpoint for understanding the finite-time synchronization process of discontinuous neural networks. Finally, a numerical example is presented to support the effectiveness of the theoretical results.

KEYWORDS:

• Hopfield neural network
• finite-time anti-synchronisation
• discontinuous activation

Acknowledgments

The  authors would like to express the sincere appreciation to the editor and anonymous reviewers for their helpful comments in improving the presentation and quality of the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was jointly supported by the National Natural Science Foundation of China [grant number 11701007], Major Program of University Natural Science Research Fund of Anhui Province [grant number KJ2020ZD32], Anhui Provincial Natural Science Foundation [grant number 1808085QA01], China Postdoctoral Science Foundation [grant number 2018M640579], and Postdoctoral Science Foundation of Anhui Province [grant numbers 2019B329, 2019B318].