An LKF method to H-infinity state estimator of neural networks with mixed interval delays

This paper explains the H ∞ state estimation problem for neural networks with mixed interval delays. Firstly, a new neural networks model is constructed, which contains an interval discrete time-varying delay and an interval natural-type time-varying delay. Secondly, a new Lyapunov-Krasoskill Functi...

Full description

Saved in:
Bibliographic Details
Main Authors: Liu, Guoquan, Luo, Chaomin, Zhou, Shumin, Luo, Xianxi, Xia, Hong
Format: Conference Proceeding
Language:English
Subjects:
Asymptotic properties
Biological neural networks
Conferences
Delay
Delays
Electronic mail
Estimators
Gain
H infinity control
H ∞ state estimator
Intervals
Mixed interval delays
Neural networks
Neurons
Neutral-type
State estimation
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper explains the H ∞ state estimation problem for neural networks with mixed interval delays. Firstly, a new neural networks model is constructed, which contains an interval discrete time-varying delay and an interval natural-type time-varying delay. Secondly, a new Lyapunov-Krasoskill Functional (LKF) is established, which contains several integral terms. Lastly, by inequality techniques, and linear matrix inequality (LMI) method, a new criterion is presented so that the error system is globally asymptotically stable with H ∞ performance. It is also shown that the estimator gain matrix can be solved by a LMI.
ISSN:2161-2927
1934-1768
DOI:10.1109/ChiCC.2016.7553928