Synchronization control of Markov jump neural networks with mixed time-varying delay and parameter uncertain based on sample point controller

  • Nuo Xu
  • Liankun SunEmail author
Original paper


This paper put forward an improved synchronization problem for neural networks with Markov jump parameters. The traditional Markov jump neural network (MJNN) only considers the basic external time-varying delays, ignoring both the distributed and leakage delays in the internal transmission of the neural network and the small time-varying errors in the mode switching of Markov probability transition rates. In this paper, we focus on the synchronization of MJNN with mixed time-varying delay. And an improved Lyapunov–Krasovskii functional is constructed. The convergence of inequalities is solved by using affine Bessel–Legendre inequalities and Wirtinger double integral inequalities. At the same time, a new method is used to optimize the mathematical geometric area of the time-varying delay and reduce the conservativeness of the system. Finally, a sample point controller is constructed to synchronize the driving system and the corresponding system.


Markov jump parameters Mixed time-varying delay Time-varying transition rates Neural network 



Project supported by the National Natural Science Foundation of China (Grant Nos. 61403278, 61503280). The authors are very indebted to the Editor and the anonymous reviewers for their insightful comments and valuable suggestions that have helped improve the academic research.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyTianjin Polytechnic UniversityTianjinChina

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