DocumentCode :
2578198
Title :
A recursive system identification method based on binary measurements
Author :
Jafari, Kian ; Juillard, Jerome ; Colinet, Eric
Author_Institution :
Dept. of Signal Process. & Electron. Syst., SUPELEC, Gif-sur-Yvette, France
fYear :
2010
fDate :
15-17 Dec. 2010
Firstpage :
1154
Lastpage :
1158
Abstract :
An online approach to parameter estimation problems based on binary observations is presented in this paper. This recursive identification method relies on a least-mean squares approach which makes it possible to estimate the coefficients of a finite-impulse response system knowing only the system input and the sign of the system output. The impulse response is identified up to a positive multiplicative constant. The role of the regulative coefficient is investigated thanks to simulated data. The proposed method is compared with another online approach: it is shown that the proposed method is competitive with the other one in terms of estimation quality and of calculation complexity.
Keywords :
FIR filters; least mean squares methods; recursive estimation; binary measurement; finite-impulse response system; least mean squares method; parameter estimation; recursive system identification method; Built-in self-test; Context; Convergence; Estimation; Least squares approximation; Noise; Parameter estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
ISSN :
0743-1546
Print_ISBN :
978-1-4244-7745-6
Type :
conf
DOI :
10.1109/CDC.2010.5717798
Filename :
5717798
Link To Document :
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