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Neural Computing and Applications

, Volume 31, Issue 1, pp 65–78 | Cite as

On passivity and robust passivity for discrete-time stochastic neural networks with randomly occurring mixed time delays

  • Jiahui Li
  • Hongli DongEmail author
  • Zidong Wang
  • Nan Hou
  • Fuad E. Alsaadi
Original Article

Abstract

In this paper, the passivity analysis problem is investigated for a class of discrete-time stochastic neural networks (DSNNs) with randomly occurring mixed time delays (ROMDs). The mixed delays comprise time-varying discrete delays, infinite-distributed delays as well as finite-distributed delays. A set of Bernoulli-distributed white sequences is used to account for the random nature of the occurrence of the mixed time delays. In addition, stochastic disturbances are taken into consideration to describe the state-dependent noises caused possibly by electronic devices and hardware implementation of neural networks. By using a combination of Lyapunov-Krasovskii functional, free-weighting matrix approach and stochastic analysis technique, we establish sufficient conditions guaranteeing the passivity performance of the underlying DSNNs. Furthermore, a delay-dependent robust passivity criterion is presented to deal with the parameter uncertainties in the DSNNs with ROMDs. A simulation example is provided to verify the effectiveness of the proposed approach.

Keywords

Discrete-time neural networks Stochastic neural networks Mixed time delays Randomly occurring time delays Robust passivity 

Notes

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61422301 and 61374127, the Northeast Petroleum University Youth Top-Notch Talent Project RC201601, the Northeast Petroleum University Innovation Foundation for Postgraduate YJSCX2016-026NEPU and the Alexander von Humboldt Foundation of Germany.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  • Jiahui Li
    • 1
    • 2
  • Hongli Dong
    • 1
    • 2
    Email author
  • Zidong Wang
    • 3
    • 4
  • Nan Hou
    • 1
    • 2
  • Fuad E. Alsaadi
    • 4
  1. 1.Institute of Complex Systems and Advanced ControlNortheast Petroleum UniversityDaqingChina
  2. 2.Heilongjiang Provincial Key Laboratory of Networking and Intelligent ControlNortheast Petroleum UniversityDaqingChina
  3. 3.Department of Computer ScienceBrunel University LondonUxbridgeUK
  4. 4.Communication Systems and Networks (CSN) Research Group, Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia

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