Title
Event-Based H∞ State Estimation for Time-Varying Stochastic Dynamical Networks With State- and Disturbance-Dependent Noises.
Abstract
In this paper, the event-based finite-horizon H∞ state estimation problem is investigated for a class of discrete time-varying stochastic dynamical networks with stateand disturbance-dependent noises [also called (x, v)-dependent noises]. An event-triggered scheme is proposed to decrease the frequency of the data transmission between the sensors and the estimator, where the signal is transmitted o...
Year
DOI
Venue
2017
10.1109/TNNLS.2016.2580601
IEEE Transactions on Neural Networks and Learning Systems
Keywords
Field
DocType
Complex networks,State estimation,Stochastic processes,Synchronization,Sensors,Symmetric matrices,Difference equations
Synchronization,Data transmission,Control theory,Stochastic process,Symmetric matrix,Complex network,Finite horizon,Mathematics,Recursion,Estimator
Journal
Volume
Issue
ISSN
28
10
2162-237X
Citations 
PageRank 
References 
3
0.40
27
Authors
4
Name
Order
Citations
PageRank
Li Sheng112515.24
Zidong Wang211003578.11
Lei Zou327214.02
Fuad E. Alsaadi41818102.89