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Neural Computing and Applications

, Volume 31, Supplement 2, pp 825–843 | Cite as

New stochastic synchronization criteria for fuzzy Markovian hybrid neural networks with random coupling strengths

  • Cheng-De ZhengEmail author
  • Nan Sun
  • Huaguang Zhang
Original Article
  • 129 Downloads

Abstract

This paper focuses on the stochastic synchronization problem for a class of fuzzy Markovian hybrid neural networks with random coupling strengths and mode-dependent mixed time delays in the mean square. First, a novel free-matrix-based single integral inequality and two novel free-matrix-based double integral inequalities are established. Next, by employing a novel augmented Lyapunov–Krasovskii functional with several mode-dependent matrices, applying the theory of Kronecker product of matrices, Barbalat’s Lemma and the new free-matrix-based integral inequalities, two delay-dependent conditions are established to achieve the globally stochastic synchronization for the mode-dependent fuzzy hybrid coupled neural networks. Finally, two numerical examples with simulation are provided to illustrate the effectiveness of the presented criteria.

Keywords

Barbalat’s Lemma Quadratic convex combination Hybrid coupled neural networks Markovian jump Mode-dependent Free-matrix-based integral inequalities 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61273022, 61433004, 61627809).

Compliance with ethical standards

Conflict of interest

The authors declared that they have no conflicts of interest to this work.

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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  1. 1.School of ScienceDalian Jiaotong UniversityDalianPeople’s Republic of China
  2. 2.School of Information Science and EngineeringNortheastern UniversityShenyangPeople’s Republic of China

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