Filter interpretation of the cost function in regularized FIR modeling

Anna Marconato; Joannes Schoukens

Samenvatting

We consider the estimation of FIR models by means of Bayesian regularization techniques. The regularization approach allows one to obtain solutions characterized by a reduced variance, at the price of slightly increasing the bias term. This is done by embedding in the problem prior information about the underlying linear dynamic system, by designing a suitable kernel matrix. In this work, we look at the same problem from a different perspective, focusing on the cost function interpretation, rather than on the kernel deﬁnition.

Originele taal-2	English
Titel	34th Benelux Meeting on Systems and Control, Center Parcs "De Vossemeren", Lommel, 24th to 26th March, 2015
Aantal pagina's	1
Status	Published - 24 mrt. 2015
Evenement	34th Benelux Meeting on Systems and Control - Vossemeren, Lommel, Belgium Duur: 24 mrt. 2015 → 26 mrt. 2015

Seminar

Seminar	34th Benelux Meeting on Systems and Control
Land/Regio	Belgium
Stad	Lommel
Periode	24/03/15 → 26/03/15

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title = "Filter interpretation of the cost function in regularized FIR modeling",

abstract = "We consider the estimation of FIR models by means of Bayesian regularization techniques. The regularization approach allows one to obtain solutions characterized by a reduced variance, at the price of slightly increasing the bias term. This is done by embedding in the problem prior information about the underlying linear dynamic system, by designing a suitable kernel matrix. In this work, we look at the same problem from a different perspective, focusing on the cost function interpretation, rather than on the kernel deﬁnition.",

keywords = "FIR models , Bayesian regularization techniques",

author = "Anna Marconato and Joannes Schoukens",

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booktitle = "34th Benelux Meeting on Systems and Control, Center Parcs {"}De Vossemeren{"}, Lommel, 24th to 26th March, 2015",

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T1 - Filter interpretation of the cost function in regularized FIR modeling

AU - Marconato, Anna

AU - Schoukens, Joannes

PY - 2015/3/24

Y1 - 2015/3/24

N2 - We consider the estimation of FIR models by means of Bayesian regularization techniques. The regularization approach allows one to obtain solutions characterized by a reduced variance, at the price of slightly increasing the bias term. This is done by embedding in the problem prior information about the underlying linear dynamic system, by designing a suitable kernel matrix. In this work, we look at the same problem from a different perspective, focusing on the cost function interpretation, rather than on the kernel deﬁnition.

AB - We consider the estimation of FIR models by means of Bayesian regularization techniques. The regularization approach allows one to obtain solutions characterized by a reduced variance, at the price of slightly increasing the bias term. This is done by embedding in the problem prior information about the underlying linear dynamic system, by designing a suitable kernel matrix. In this work, we look at the same problem from a different perspective, focusing on the cost function interpretation, rather than on the kernel deﬁnition.

KW - FIR models

KW - Bayesian regularization techniques

M3 - Meeting abstract (Book)

BT - 34th Benelux Meeting on Systems and Control, Center Parcs "De Vossemeren", Lommel, 24th to 26th March, 2015

T2 - 34th Benelux Meeting on Systems and Control

Y2 - 24 March 2015 through 26 March 2015

ER -

Filter interpretation of the cost function in regularized FIR modeling

Samenvatting

Seminar

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