DocumentCode
3250202
Title
CAR identification from nonuniformly sampled values using LMS
Author
Lahalle, Elisabeth ; Poulton, Daniel ; Oksman, Jacques
Author_Institution
Dept. of Signal Process. & Electron. Syst., Supelec, Gif sur Yvette, France
fYear
2005
fDate
7-10 Aug. 2005
Firstpage
199
Abstract
In this paper a new CAR LMS identification algorithm for irregularly sampled signals is proposed. The proposed method uses implicit numerical integration formulas to build an adaptive predictor from the stochastic differential equation of the CAR model. Formulas that may adapt to the irregular sampling case have been considered. The performances of the proposed method have been evaluated for both Poisson and jitter sampling schemes.
Keywords
Poisson distribution; continuous time systems; differential equations; integration; least mean squares methods; prediction theory; signal sampling; CAR LMS identification algorithm; Poisson schemes; adaptive predictor; jitter sampling schemes; nonuniformly sampled values; numerical integration formulas; stochastic differential equation; Differential equations; Jitter; Laser modes; Least squares approximation; Predictive models; Signal processing; Signal processing algorithms; Signal sampling; State-space methods; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2005. 48th Midwest Symposium on
Print_ISBN
0-7803-9197-7
Type
conf
DOI
10.1109/MWSCAS.2005.1594073
Filename
1594073
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