Circuits, Systems, and Signal Processing

, Volume 38, Issue 2, pp 874–890 | Cite as

Decentralized Adaptive Event-Triggered Synchronization of Neutral Neural Networks with Time-Varying Delays

  • Tao LiEmail author
  • Yaobao Yu
  • Ting Wang
  • Shumin Fei
Short Paper


In this work, the adaptive event-triggered synchronization in a class of master–slave neutral neural networks with time-varying delay is studied. The design of decentralized event-triggered scheme is proposed, which only utilizes local available information to determine the released instants from multiple sensors to a centralized controller. Different from existing ones, the triggering thresholds depend on real-time performance of controlled system. Together with some novel Lyapunov terms, an augmented Lyapunov–Krasovskii functional is constructed, in which the interconnection between time delays can be fully utilized. In particular, a less conservative condition on controller gain is obtained in terms of linear matrix inequalities. Finally, the derived results are verified by resorting to two numerical examples.


Neutral neural networks Adaptive event-triggered scheme Synchronization Time-varying delay 


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingPeople’s Republic of China
  2. 2.School of Information Science and TechnologyNanjing Forestry UniversityNanjingPeople’s Republic of China
  3. 3.School of AutomationSoutheast UniversityNanjingPeople’s Republic of China

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