Adaptive IIR filtering via a recursive total instrumental variable algorithm

Da-Zheng Feng; Wei Xing Zheng; Gianluca Setti; Nam Ling

Adaptive IIR filtering via a recursive total instrumental variable algorithm

Da-Zheng Feng, Wei Xing Zheng, Gianluca Setti, Nam Ling

Research output: Chapter in Book / Conference Paper › Conference Paper

Abstract

Adaptive IIR filtering in the case where noise exists in both the input and output of the system amounts to solving over-determined normal equations. In this paper a recursive total instrumental-variable (RTIV) algorithm is proposed for tracking the total least-squares (TLS) solution of the normal equations in the over-determined instrumental-variable methods. It is shown that the weight vector in the RTIV algorithm converges to the direction parallel to the singular vector associated with the smallest singular value of the augmented cross-correlation matrix. Moreover, the estimated parameters of the adaptive IIR filter are optimal in the TLS sense and its noise rejection capability is superior to that of the least-squares based algorithms. The appealing behavior of the RTIV algorithm for noisy adaptive IIR filtering is substantiated by simulation results.

Original language	English
Title of host publication	Proceedings of 2007 IEEE International Symposium on Circuits and Systems
Publisher	IEEE
Number of pages	4
ISBN (Print)	1424409217
Publication status	Published - 2007
Event	IEEE International Symposium on Circuits and Systems - Duration: 20 May 2012 → …

Conference

Conference	IEEE International Symposium on Circuits and Systems
Period	20/05/12 → …

Keywords

algorithms
recursive functions
equations
instrumental variables (statistics)
electromagnetic noise
least squares

Cite this

@inproceedings{c31294d5dba54b9799e9848a29f0dc88,

title = "Adaptive IIR filtering via a recursive total instrumental variable algorithm",

abstract = "Adaptive IIR filtering in the case where noise exists in both the input and output of the system amounts to solving over-determined normal equations. In this paper a recursive total instrumental-variable (RTIV) algorithm is proposed for tracking the total least-squares (TLS) solution of the normal equations in the over-determined instrumental-variable methods. It is shown that the weight vector in the RTIV algorithm converges to the direction parallel to the singular vector associated with the smallest singular value of the augmented cross-correlation matrix. Moreover, the estimated parameters of the adaptive IIR filter are optimal in the TLS sense and its noise rejection capability is superior to that of the least-squares based algorithms. The appealing behavior of the RTIV algorithm for noisy adaptive IIR filtering is substantiated by simulation results.",

keywords = "algorithms, recursive functions, equations, instrumental variables (statistics), electromagnetic noise, least squares",

author = "Da-Zheng Feng and Zheng, {Wei Xing} and Gianluca Setti and Nam Ling",

year = "2007",

language = "English",

isbn = "1424409217",

booktitle = "Proceedings of 2007 IEEE International Symposium on Circuits and Systems",

publisher = "IEEE",

note = "IEEE International Symposium on Circuits and Systems ; Conference date: 20-05-2012",

}

TY - GEN

T1 - Adaptive IIR filtering via a recursive total instrumental variable algorithm

AU - Feng, Da-Zheng

AU - Zheng, Wei Xing

AU - Setti, Gianluca

AU - Ling, Nam

PY - 2007

Y1 - 2007

N2 - Adaptive IIR filtering in the case where noise exists in both the input and output of the system amounts to solving over-determined normal equations. In this paper a recursive total instrumental-variable (RTIV) algorithm is proposed for tracking the total least-squares (TLS) solution of the normal equations in the over-determined instrumental-variable methods. It is shown that the weight vector in the RTIV algorithm converges to the direction parallel to the singular vector associated with the smallest singular value of the augmented cross-correlation matrix. Moreover, the estimated parameters of the adaptive IIR filter are optimal in the TLS sense and its noise rejection capability is superior to that of the least-squares based algorithms. The appealing behavior of the RTIV algorithm for noisy adaptive IIR filtering is substantiated by simulation results.

AB - Adaptive IIR filtering in the case where noise exists in both the input and output of the system amounts to solving over-determined normal equations. In this paper a recursive total instrumental-variable (RTIV) algorithm is proposed for tracking the total least-squares (TLS) solution of the normal equations in the over-determined instrumental-variable methods. It is shown that the weight vector in the RTIV algorithm converges to the direction parallel to the singular vector associated with the smallest singular value of the augmented cross-correlation matrix. Moreover, the estimated parameters of the adaptive IIR filter are optimal in the TLS sense and its noise rejection capability is superior to that of the least-squares based algorithms. The appealing behavior of the RTIV algorithm for noisy adaptive IIR filtering is substantiated by simulation results.

KW - algorithms

KW - recursive functions

KW - equations

KW - instrumental variables (statistics)

KW - electromagnetic noise

KW - least squares

UR - http://handle.uws.edu.au:8081/1959.7/45135

M3 - Conference Paper

SN - 1424409217

BT - Proceedings of 2007 IEEE International Symposium on Circuits and Systems

PB - IEEE

T2 - IEEE International Symposium on Circuits and Systems

Y2 - 20 May 2012

ER -

Adaptive IIR filtering via a recursive total instrumental variable algorithm

Abstract

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Keywords

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