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Event-triggered stochastic synchronization in finite time for delayed semi-Markovian jump neural networks with discontinuous activations

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Abstract

In this paper, the global stochastic synchronization in finite time is discussed for discontinuous semi-Markovian switching neural networks with mixed time-varying delays under stochastic disturbance based on event-triggered non-fragile control scheme. By applying the novel hybrid controller, which is composed of the event-triggered controller, the non-fragile controller and the switching state-feedback controller, the global stochastic synchronization goals in finite time are achieved. Under Filippov differential inclusion framework, based on non-smooth analysis theory, general free-weighting matrix method, Lyapunov–Krasovskii functional approach and inequality analysis technique, the global stochastic synchronization conditions in finite time are addressed in terms of linear matrix inequalities. Moreover, the expressions about the upper bound of stochastic settling time are explicitly developed. Finally, two numerical examples are provided to illustrate the feasibility of the proposed control scheme and the validity of theoretical results.

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Acknowledgements

The authors would like to thank the associate editors and the reviewers for their insightful and constructive comments, which helped to enrich the content and improve the presentation of the results in this paper. This work was supported by the Natural Science Foundation of Hebei Province of China (A2018203288), High Level Talent Support Project of Hebei Province of China (C2015003054) and the Postgraduate Innovation Project of Hebei Province of China (CXZZSS2018048).

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Correspondence to Huaiqin Wu.

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Liu, M., Wu, H. & Zhao, W. Event-triggered stochastic synchronization in finite time for delayed semi-Markovian jump neural networks with discontinuous activations . Comp. Appl. Math. 39, 118 (2020). https://doi.org/10.1007/s40314-020-01146-2

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