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
Link To Document :
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