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

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

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2622125