Optimal generalized regularization approach to parameter identification by using band-limited input signal

A. Sano; H. Tsuji; Hiromitsu Ohmori

doi:10.1109/ICASSP.1992.226615

Optimal generalized regularization approach to parameter identification by using band-limited input signal

A. Sano, H. Tsuji, Hiromitsu Ohmori

Department of System Design Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

This paper presents generalized regularization based on generalized singular value decomposition is presented in order to attain stabilized identification of an impulse response or transfer function by using bandlimited input signals. The optimal regularization parameters can be determined so as to minimize a new Bayesian information criterion, by which the smoothness order for the estimated impulse response can be given as well. In the case of the transfer function, a new idea is employed in estimating a system output to reduce the problem to the above linear regression problem. It is shown that the optimal regularization is closely related to the optimal choice of the initial conditions in the recursive least squares estimation and also to the optimal truncation of generalized singular values.

Original language	English
Title of host publication	ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	333-336
Number of pages	4
Volume	5
ISBN (Electronic)	0780305329
DOIs	https://doi.org/10.1109/ICASSP.1992.226615
Publication status	Published - 1992
Event	1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992 - San Francisco, United States Duration: 1992 Mar 23 → 1992 Mar 26

Other

Other	1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992
Country	United States
City	San Francisco
Period	92/3/23 → 92/3/26

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

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Sano, A., Tsuji, H., & Ohmori, H. (1992). Optimal generalized regularization approach to parameter identification by using band-limited input signal. In ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing (Vol. 5, pp. 333-336). [226615] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.1992.226615

Optimal generalized regularization approach to parameter identification by using band-limited input signal. / Sano, A.; Tsuji, H.; Ohmori, Hiromitsu.

ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. Vol. 5 Institute of Electrical and Electronics Engineers Inc., 1992. p. 333-336 226615.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Sano, A, Tsuji, H & Ohmori, H 1992, Optimal generalized regularization approach to parameter identification by using band-limited input signal. in ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. vol. 5, 226615, Institute of Electrical and Electronics Engineers Inc., pp. 333-336, 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992, San Francisco, United States, 92/3/23. https://doi.org/10.1109/ICASSP.1992.226615

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abstract = "This paper presents generalized regularization based on generalized singular value decomposition is presented in order to attain stabilized identification of an impulse response or transfer function by using bandlimited input signals. The optimal regularization parameters can be determined so as to minimize a new Bayesian information criterion, by which the smoothness order for the estimated impulse response can be given as well. In the case of the transfer function, a new idea is employed in estimating a system output to reduce the problem to the above linear regression problem. It is shown that the optimal regularization is closely related to the optimal choice of the initial conditions in the recursive least squares estimation and also to the optimal truncation of generalized singular values.",

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AU - Tsuji, H.

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N2 - This paper presents generalized regularization based on generalized singular value decomposition is presented in order to attain stabilized identification of an impulse response or transfer function by using bandlimited input signals. The optimal regularization parameters can be determined so as to minimize a new Bayesian information criterion, by which the smoothness order for the estimated impulse response can be given as well. In the case of the transfer function, a new idea is employed in estimating a system output to reduce the problem to the above linear regression problem. It is shown that the optimal regularization is closely related to the optimal choice of the initial conditions in the recursive least squares estimation and also to the optimal truncation of generalized singular values.

AB - This paper presents generalized regularization based on generalized singular value decomposition is presented in order to attain stabilized identification of an impulse response or transfer function by using bandlimited input signals. The optimal regularization parameters can be determined so as to minimize a new Bayesian information criterion, by which the smoothness order for the estimated impulse response can be given as well. In the case of the transfer function, a new idea is employed in estimating a system output to reduce the problem to the above linear regression problem. It is shown that the optimal regularization is closely related to the optimal choice of the initial conditions in the recursive least squares estimation and also to the optimal truncation of generalized singular values.

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BT - ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing

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Y2 - 23 March 1992 through 26 March 1992

ER -

Optimal generalized regularization approach to parameter identification by using band-limited input signal

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