An alternative solution to the dynamically regularized RLS algorithm

Feiran Yang; Jun Yang; Felix Albu

doi:10.1109/APSIPAASC47483.2019.9023073

An alternative solution to the dynamically regularized RLS algorithm

Feiran Yang, Jun Yang, Felix Albu

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

1 Citation (Scopus)

Abstract

The recursive least-squares (RLS) algorithm should be explicitly regularized to achieve a satisfactory performance when the signal-to-noise ratio is low. However, a direct implementation of the involved matrix inversion results in a high complexity. In this paper, we present a recursive approach to the matrix inversion of the dynamically regularized RLS algorithm by exploiting the special structure of the correlation matrix. The proposed method has a similar complexity to the standard RLS algorithm. Moreover, the new method provides an exact solution for a fixed regularization parameter, and it has a good accuracy even for a slowly time-varying regularization parameter. Simulation results confirm the effectiveness of the new method.

Original language	English
Title of host publication	2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1072-1075
Number of pages	4
ISBN (Electronic)	9781728132488
DOIs	https://doi.org/10.1109/APSIPAASC47483.2019.9023073
Publication status	Published - Nov 2019
Externally published	Yes
Event	2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 - Lanzhou, China Duration: Nov 18 2019 → Nov 21 2019

Publication series

Name	2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019

Conference

Conference	2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
Country/Territory	China
City	Lanzhou
Period	11/18/19 → 11/21/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

ASJC Scopus Subject Areas

Information Systems

Access to Document

10.1109/APSIPAASC47483.2019.9023073

Cite this

Yang, F., Yang, J., & Albu, F. (2019). An alternative solution to the dynamically regularized RLS algorithm. In 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 (pp. 1072-1075). Article 9023073 (2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APSIPAASC47483.2019.9023073

Yang, Feiran ; Yang, Jun ; Albu, Felix. / An alternative solution to the dynamically regularized RLS algorithm. 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1072-1075 (2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019).

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title = "An alternative solution to the dynamically regularized RLS algorithm",

abstract = "The recursive least-squares (RLS) algorithm should be explicitly regularized to achieve a satisfactory performance when the signal-to-noise ratio is low. However, a direct implementation of the involved matrix inversion results in a high complexity. In this paper, we present a recursive approach to the matrix inversion of the dynamically regularized RLS algorithm by exploiting the special structure of the correlation matrix. The proposed method has a similar complexity to the standard RLS algorithm. Moreover, the new method provides an exact solution for a fixed regularization parameter, and it has a good accuracy even for a slowly time-varying regularization parameter. Simulation results confirm the effectiveness of the new method.",

author = "Feiran Yang and Jun Yang and Felix Albu",

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year = "2019",

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doi = "10.1109/APSIPAASC47483.2019.9023073",

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Yang, F, Yang, J & Albu, F 2019, An alternative solution to the dynamically regularized RLS algorithm. in 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019., 9023073, 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1072-1075, 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019, Lanzhou, China, 11/18/19. https://doi.org/10.1109/APSIPAASC47483.2019.9023073

An alternative solution to the dynamically regularized RLS algorithm. / Yang, Feiran; Yang, Jun; Albu, Felix.
2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1072-1075 9023073 (2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019).

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

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T1 - An alternative solution to the dynamically regularized RLS algorithm

AU - Yang, Feiran

AU - Yang, Jun

AU - Albu, Felix

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N2 - The recursive least-squares (RLS) algorithm should be explicitly regularized to achieve a satisfactory performance when the signal-to-noise ratio is low. However, a direct implementation of the involved matrix inversion results in a high complexity. In this paper, we present a recursive approach to the matrix inversion of the dynamically regularized RLS algorithm by exploiting the special structure of the correlation matrix. The proposed method has a similar complexity to the standard RLS algorithm. Moreover, the new method provides an exact solution for a fixed regularization parameter, and it has a good accuracy even for a slowly time-varying regularization parameter. Simulation results confirm the effectiveness of the new method.

AB - The recursive least-squares (RLS) algorithm should be explicitly regularized to achieve a satisfactory performance when the signal-to-noise ratio is low. However, a direct implementation of the involved matrix inversion results in a high complexity. In this paper, we present a recursive approach to the matrix inversion of the dynamically regularized RLS algorithm by exploiting the special structure of the correlation matrix. The proposed method has a similar complexity to the standard RLS algorithm. Moreover, the new method provides an exact solution for a fixed regularization parameter, and it has a good accuracy even for a slowly time-varying regularization parameter. Simulation results confirm the effectiveness of the new method.

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Yang F, Yang J, Albu F. An alternative solution to the dynamically regularized RLS algorithm. In 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1072-1075. 9023073. (2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019). doi: 10.1109/APSIPAASC47483.2019.9023073

An alternative solution to the dynamically regularized RLS algorithm

Abstract

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Conference

Bibliographical note

ASJC Scopus Subject Areas

Access to Document

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