Event-Based State Estimation for Neural Network With Time-Varying Delay and Infinite-Distributed Delay

DU Yuwei; LI Bing; SONG Qiankun

doi:10.21656/1000-0887.400377

Volume 41 Issue 8

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Article Navigation > Applied Mathematics and Mechanics > 2020 > 41(8): 887-898

DU Yuwei, LI Bing, SONG Qiankun. Event-Based State Estimation for Neural Network With Time-Varying Delay and Infinite-Distributed Delay[J]. Applied Mathematics and Mechanics, 2020, 41(8): 887-898. doi: 10.21656/1000-0887.400377

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Event-Based State Estimation for Neural Network With Time-Varying Delay and Infinite-Distributed Delay

doi: 10.21656/1000-0887.400377

College of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing 400074, P.R. China

Funds: The National Natural Science Foundation of China(61773004)

Received Date: 2019-12-13
Rev Recd Date: 2020-01-04
Publish Date: 2020-08-01

Abstract

Abstract

The event-based state estimation problem was investigated for a class of neural networks with mixed delays. A novel event-triggering scheme depending on both the output and exponential decay function was designed to reduce the frequency of updating. In view of both the mixed delays and the event-triggering properties, a new state estimation error system was built. The exponential stability of the error system was derived with the Lyapunov function and the inequality technique. The Zeno phenomenon was analyzed and excluded. Finally, a numerical example and its simulations were presented to illustrate the effectiveness of the proposed approach.
- mixed delay,
- state estimation,
- event-triggering control,
- Zeno behavior,
- Lyapunov function

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References

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