New stable IIR modeling of long FIR filters with Low complexity

Jie Chen; Keshab K Parhi

doi:10.1109/ACSSC.2008.5074704

New stable IIR modeling of long FIR filters with Low complexity

Jie Chen, Keshab K Parhi

Electrical and Computer Engineering

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

Abstract

This paper presents a new efficient method for stable polezero modeling of long finite impulse response (FIR) filters. The proposed method is based on the formulation of a generalized system identification problem using the minimum mean-square error (MMSE) criterion. A computationally efficient MMSE solution is then derived by exploiting the structured matrices. The proposed method is general and applicable to cases with unequal numbers of poles and zeros. Compared with the Generalized ARMA-Levinson algorithm, the proposed method has lower computational complexity without loss of accuracy. Numerical results are provided to demonstrate the effectiveness of the proposed method.

Original language	English (US)
Title of host publication	2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Pages	1649-1653
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2008.5074704
State	Published - Dec 1 2008
Event	2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008 - Pacific Grove, CA, United States Duration: Oct 26 2008 → Oct 29 2008

Other

Other	2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Country/Territory	United States
City	Pacific Grove, CA
Period	10/26/08 → 10/29/08

Keywords

Computational complexity
Levinson
Minimum mean-square error (MMSE)
Pole-zero modeling
Structured matrices

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10.1109/ACSSC.2008.5074704

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title = "New stable IIR modeling of long FIR filters with Low complexity",

abstract = "This paper presents a new efficient method for stable polezero modeling of long finite impulse response (FIR) filters. The proposed method is based on the formulation of a generalized system identification problem using the minimum mean-square error (MMSE) criterion. A computationally efficient MMSE solution is then derived by exploiting the structured matrices. The proposed method is general and applicable to cases with unequal numbers of poles and zeros. Compared with the Generalized ARMA-Levinson algorithm, the proposed method has lower computational complexity without loss of accuracy. Numerical results are provided to demonstrate the effectiveness of the proposed method.",

keywords = "Computational complexity, Levinson, Minimum mean-square error (MMSE), Pole-zero modeling, Structured matrices",

author = "Jie Chen and Parhi, {Keshab K}",

year = "2008",

month = dec,

day = "1",

doi = "10.1109/ACSSC.2008.5074704",

language = "English (US)",

isbn = "9781424429417",

pages = "1649--1653",

booktitle = "2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008",

note = "2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008 ; Conference date: 26-10-2008 Through 29-10-2008",

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TY - GEN

T1 - New stable IIR modeling of long FIR filters with Low complexity

AU - Chen, Jie

AU - Parhi, Keshab K

PY - 2008/12/1

Y1 - 2008/12/1

N2 - This paper presents a new efficient method for stable polezero modeling of long finite impulse response (FIR) filters. The proposed method is based on the formulation of a generalized system identification problem using the minimum mean-square error (MMSE) criterion. A computationally efficient MMSE solution is then derived by exploiting the structured matrices. The proposed method is general and applicable to cases with unequal numbers of poles and zeros. Compared with the Generalized ARMA-Levinson algorithm, the proposed method has lower computational complexity without loss of accuracy. Numerical results are provided to demonstrate the effectiveness of the proposed method.

AB - This paper presents a new efficient method for stable polezero modeling of long finite impulse response (FIR) filters. The proposed method is based on the formulation of a generalized system identification problem using the minimum mean-square error (MMSE) criterion. A computationally efficient MMSE solution is then derived by exploiting the structured matrices. The proposed method is general and applicable to cases with unequal numbers of poles and zeros. Compared with the Generalized ARMA-Levinson algorithm, the proposed method has lower computational complexity without loss of accuracy. Numerical results are provided to demonstrate the effectiveness of the proposed method.

KW - Computational complexity

KW - Levinson

KW - Minimum mean-square error (MMSE)

KW - Pole-zero modeling

KW - Structured matrices

UR - http://www.scopus.com/inward/record.url?scp=70349671017&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70349671017&partnerID=8YFLogxK

U2 - 10.1109/ACSSC.2008.5074704

DO - 10.1109/ACSSC.2008.5074704

M3 - Conference contribution

AN - SCOPUS:70349671017

SN - 9781424429417

SP - 1649

EP - 1653

BT - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008

T2 - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008

Y2 - 26 October 2008 through 29 October 2008

ER -

New stable IIR modeling of long FIR filters with Low complexity

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