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Dynamic event-triggered state estimation for time-delayed spatial-temporal networks under encoding-decoding scheme.

Authors :
Sun, Jie
Shen, Bo
Liu, Yurong
Alsaadi, Fuad E.
Source :
Neurocomputing. Aug2022, Vol. 500, p868-876. 9p.
Publication Year :
2022

Abstract

This paper is concerned with the dynamic event-triggered state estimation problem for a class of spatial-temporal networks (STNs) with time-varying delays under an encoding-decoding strategy. For the sake of reducing the unnecessary resources wastes, we establish a dynamic event-triggered mechanism to determine whether the current measurement output data is transmitted to the filter, where the threshold is dynamically adjusted according to a certain rule. In order to enhance the robustness of signal transmission, an encoding-decoding strategy is exploited in the process of the data transmission. To be specific, the original signals encoded as a bit string are transmitted through binary symmetric channels with certain crossover probabilities and then restored by a decoder at the receiver. By constructing Lyapunov-Krasovskii functional, we obtain a sufficient condition to ensure that the estimation error system is exponential mean square ultimately bounded. Subsequently, the desired state estimator is designed in terms of the solution to a certain matrix inequality. Finally, a numerical example is shown to demonstrate that the proposed state estimator is valid for time-delayed STNs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
500
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
157561558
Full Text :
https://doi.org/10.1016/j.neucom.2022.05.062