Modified bias compensation recursive least-squares method for noisy FIR adaptive filtering

Li Juan Jia; Shunshoku Kanae; Zi Jiang Yang; Kiyoshi Wada

Modified bias compensation recursive least-squares method for noisy FIR adaptive filtering

Li Juan Jia^*, Shunshoku Kanae, Zi Jiang Yang, Kiyoshi Wada

^*Corresponding author for this work

School of Information and Electronics

Department of Electrical and Electronic Systems Engineering

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

In this paper a modified bias compensation recursive least-squares (MBCRLS) method is proposed to deal with the task of adaptive FIR filtering with noisy input-output data. This method is similar to the BCRLS method which is proposed by authors recently in terms of use of introducing an auxiliary estimator but a different form with that one in BCRLS method. Several modified points both in theoretical discussion and recursive computing aspects in the new MBCRLS method lead to a reduction in computing cost and simple, readable and understandable derivation. Simulation results are conductive to verify the discussions.

Original language	English
Pages (from-to)	15-20
Number of pages	6
Journal	Research Reports on Information Science and Electrical Engineering of Kyushu University
Volume	12
Issue number	1
Publication status	Published - Mar 2007

Keywords

Adaptive filters
Bias compensation
Noisy FIR system
Recursive least squares parameter estimation

Cite this

@article{1a72ccfe277549d38c6e50f38273ad14,

title = "Modified bias compensation recursive least-squares method for noisy FIR adaptive filtering",

abstract = "In this paper a modified bias compensation recursive least-squares (MBCRLS) method is proposed to deal with the task of adaptive FIR filtering with noisy input-output data. This method is similar to the BCRLS method which is proposed by authors recently in terms of use of introducing an auxiliary estimator but a different form with that one in BCRLS method. Several modified points both in theoretical discussion and recursive computing aspects in the new MBCRLS method lead to a reduction in computing cost and simple, readable and understandable derivation. Simulation results are conductive to verify the discussions.",

keywords = "Adaptive filters, Bias compensation, Noisy FIR system, Recursive least squares parameter estimation",

author = "Jia, {Li Juan} and Shunshoku Kanae and Yang, {Zi Jiang} and Kiyoshi Wada",

year = "2007",

month = mar,

language = "English",

volume = "12",

pages = "15--20",

journal = "Research Reports on Information Science and Electrical Engineering of Kyushu University",

issn = "1342-3819",

publisher = "Kyushu University, Faculty of Science",

number = "1",

}

TY - JOUR

T1 - Modified bias compensation recursive least-squares method for noisy FIR adaptive filtering

AU - Jia, Li Juan

AU - Kanae, Shunshoku

AU - Yang, Zi Jiang

AU - Wada, Kiyoshi

PY - 2007/3

Y1 - 2007/3

N2 - In this paper a modified bias compensation recursive least-squares (MBCRLS) method is proposed to deal with the task of adaptive FIR filtering with noisy input-output data. This method is similar to the BCRLS method which is proposed by authors recently in terms of use of introducing an auxiliary estimator but a different form with that one in BCRLS method. Several modified points both in theoretical discussion and recursive computing aspects in the new MBCRLS method lead to a reduction in computing cost and simple, readable and understandable derivation. Simulation results are conductive to verify the discussions.

AB - In this paper a modified bias compensation recursive least-squares (MBCRLS) method is proposed to deal with the task of adaptive FIR filtering with noisy input-output data. This method is similar to the BCRLS method which is proposed by authors recently in terms of use of introducing an auxiliary estimator but a different form with that one in BCRLS method. Several modified points both in theoretical discussion and recursive computing aspects in the new MBCRLS method lead to a reduction in computing cost and simple, readable and understandable derivation. Simulation results are conductive to verify the discussions.

KW - Adaptive filters

KW - Bias compensation

KW - Noisy FIR system

KW - Recursive least squares parameter estimation

UR - http://www.scopus.com/inward/record.url?scp=34548072780&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:34548072780

SN - 1342-3819

VL - 12

SP - 15

EP - 20

JO - Research Reports on Information Science and Electrical Engineering of Kyushu University

JF - Research Reports on Information Science and Electrical Engineering of Kyushu University

IS - 1

ER -

Modified bias compensation recursive least-squares method for noisy FIR adaptive filtering

Abstract

Keywords

Other files and links

Fingerprint

Cite this