DocumentCode :
2622125
Title :
Empirical Bayesian finite impulse response modeling
Author :
Nounou, Mohamed N.
Author_Institution :
Dept. of Chem. & Pet. Eng., United Arab Emirates Univ., Abu Dhabi, United Arab Emirates
Volume :
6
fYear :
2003
fDate :
9-12 Dec. 2003
Firstpage :
6480
Abstract :
This paper presents a Bayesian modeling technique, called empirical Bayesian finite response (EBFIR) modeling, that helps deal with the collinearity problem usually encountered in FIR models, and helps improve the estimation accuracy of their coefficients. The developed technique iteratively solves for the prior density used in estimation and the FIR coefficients. The advantages of the developed EBFIR modeling technique are also illustrated though a simulated example.
Keywords :
Bayes methods; iterative methods; large-scale systems; parameter estimation; process control; transient response; Bayesian estimation; FIR coefficients; FIR models; collinearity problem; empirical Bayesian finite impulse response modeling; iterative method; Bayesian methods; Chemical engineering; Density functional theory; Density measurement; Finite impulse response filter; Large-scale systems; Matrix decomposition; Parameter estimation; Petroleum; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
ISSN :
0191-2216
Print_ISBN :
0-7803-7924-1
Type :
conf
DOI :
10.1109/CDC.2003.1272387
Filename :
1272387
Link To Document :
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