On unbiased identification of autoregressive signals with noisy measurements

Youshen Xia; Wei Xing Zheng

doi:10.1109/ISCAS.2015.7169107

On unbiased identification of autoregressive signals with noisy measurements

Youshen Xia, Wei Xing Zheng

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

1 Citation (Scopus)

Abstract

![CDATA[The problem of identification of autoregressive (AR) signals with noisy measurements is considered. A new algorithm is proposed to estimate the AR parameters. To cope with the effect of the measurement noise that causes a bias in the least-squares estimate of the AR parameters, an efficient procedure is developed for estimating the measurement noise variance. The proposed identification algorithm is implemented via the Newton iterative scheme and is able to produce better parameter estimates. A numerical example is presented to show the efficiency of the new identification algorithm for noisy AR signals.]]

Original language	English
Title of host publication	Proceedings 2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015, Lisbon, Portugal, 24-27 May 2015
Publisher	IEEE
Pages	2157-2160
Number of pages	4
ISBN (Print)	9781479983926
DOIs	https://doi.org/10.1109/ISCAS.2015.7169107
Publication status	Published - 2015
Event	IEEE International Symposium on Circuits and Systems - Duration: 24 May 2015 → …

Publication series

Name
ISSN (Print)	0271-4310

Conference

Conference	IEEE International Symposium on Circuits and Systems
Period	24/05/15 → …

Keywords

Newton-Raphson method
algorithms
signal processing

Access to Document

10.1109/ISCAS.2015.7169107

Cite this

@inproceedings{3e8893e0ce56475c86ae449c0f2883a2,

title = "On unbiased identification of autoregressive signals with noisy measurements",

abstract = "![CDATA[The problem of identification of autoregressive (AR) signals with noisy measurements is considered. A new algorithm is proposed to estimate the AR parameters. To cope with the effect of the measurement noise that causes a bias in the least-squares estimate of the AR parameters, an efficient procedure is developed for estimating the measurement noise variance. The proposed identification algorithm is implemented via the Newton iterative scheme and is able to produce better parameter estimates. A numerical example is presented to show the efficiency of the new identification algorithm for noisy AR signals.]]",

keywords = "Newton-Raphson method, algorithms, signal processing",

author = "Youshen Xia and Zheng, {Wei Xing}",

year = "2015",

doi = "10.1109/ISCAS.2015.7169107",

language = "English",

isbn = "9781479983926",

publisher = "IEEE",

pages = "2157--2160",

booktitle = "Proceedings 2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015, Lisbon, Portugal, 24-27 May 2015",

note = "IEEE International Symposium on Circuits and Systems ; Conference date: 24-05-2015",

}

TY - GEN

T1 - On unbiased identification of autoregressive signals with noisy measurements

AU - Xia, Youshen

AU - Zheng, Wei Xing

PY - 2015

Y1 - 2015

N2 - ![CDATA[The problem of identification of autoregressive (AR) signals with noisy measurements is considered. A new algorithm is proposed to estimate the AR parameters. To cope with the effect of the measurement noise that causes a bias in the least-squares estimate of the AR parameters, an efficient procedure is developed for estimating the measurement noise variance. The proposed identification algorithm is implemented via the Newton iterative scheme and is able to produce better parameter estimates. A numerical example is presented to show the efficiency of the new identification algorithm for noisy AR signals.]]

AB - ![CDATA[The problem of identification of autoregressive (AR) signals with noisy measurements is considered. A new algorithm is proposed to estimate the AR parameters. To cope with the effect of the measurement noise that causes a bias in the least-squares estimate of the AR parameters, an efficient procedure is developed for estimating the measurement noise variance. The proposed identification algorithm is implemented via the Newton iterative scheme and is able to produce better parameter estimates. A numerical example is presented to show the efficiency of the new identification algorithm for noisy AR signals.]]

KW - Newton-Raphson method

KW - algorithms

KW - signal processing

UR - http://handle.uws.edu.au:8081/1959.7/uws:32712

UR - http://www.iscas2015.org/

U2 - 10.1109/ISCAS.2015.7169107

DO - 10.1109/ISCAS.2015.7169107

M3 - Conference Paper

SN - 9781479983926

SP - 2157

EP - 2160

BT - Proceedings 2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015, Lisbon, Portugal, 24-27 May 2015

PB - IEEE

T2 - IEEE International Symposium on Circuits and Systems

Y2 - 24 May 2015

ER -

On unbiased identification of autoregressive signals with noisy measurements

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