DocumentCode
2266641
Title
Distributed parameter estimation in sensor networks based on stochastic approximation
Author
Lei, Jinlong ; Chen, Han-Fu
Author_Institution
The Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, P.R. China
fYear
2015
fDate
28-30 July 2015
Firstpage
7487
Lastpage
7492
Abstract
A distributed stochastic approximation algorithm with expanding truncations (DSAAWET) is proposed to estimate the unknown parameter linearly appearing in the sensor networks. Each agent updates its local estimate by averaging its neighbors´ estimates with weights and by processing its local current observation. The estimates are shown to converge to the true parameter with probability one. A numerical example is given to demonstrate the obtained theoretic result.
Keywords
Convergence; Estimation; Least squares approximations; Noise; Parameter estimation; Stochastic processes; Distributed parameter estimation; linear observation model; sensor networks; stochastic approximation;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2015 34th Chinese
Conference_Location
Hangzhou, China
Type
conf
DOI
10.1109/ChiCC.2015.7260826
Filename
7260826
Link To Document