Estimation of Noise Variance from Noisy Measurements of AR and ARMA Systems: Application to Blind Identification of Linear Time-Invariant Systems
Summary :
In many applications involving the processing of noisy signals, it is desired to know the noise variance. This paper proposes a new method for estimating the noise variance from the signals of autoregressive (AR) and autoregressive moving-average (ARMA) systems corrupted by additive white noise. The method proposed here uses the low-order Yule-Walker (LOYW) equations and the lattice filter (LF) algorithm for the estimation of noise variance from the noisy output measurements of AR and ARMA systems, respectively. Two techniques are proposed here: iterative technique and recursive one. The accuracy of the methods depends on SNR levels, more specifically on the inherent accuracy of the Yule-Walker and lattice filter methods for signal plus noise system. The estimated noise variance is used for the blind indentification of AR and ARMA systems. Finally, to demonstrate the effectiveness of the method proposed here many numerical results are presented.
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- IEICE TRANSACTIONS on Fundamentals Vol.E77-A No.5 pp.847-855
- Publication Date
- 1994/05/25
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- Special Section PAPER (Special Section on Signal Processing and System Theory)
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Takashi YAHAGI, Md.Kamrul HASAN, "Estimation of Noise Variance from Noisy Measurements of AR and ARMA Systems: Application to Blind Identification of Linear Time-Invariant Systems" in IEICE TRANSACTIONS on Fundamentals,
vol. E77-A, no. 5, pp. 847-855, May 1994, doi: .
Abstract: In many applications involving the processing of noisy signals, it is desired to know the noise variance. This paper proposes a new method for estimating the noise variance from the signals of autoregressive (AR) and autoregressive moving-average (ARMA) systems corrupted by additive white noise. The method proposed here uses the low-order Yule-Walker (LOYW) equations and the lattice filter (LF) algorithm for the estimation of noise variance from the noisy output measurements of AR and ARMA systems, respectively. Two techniques are proposed here: iterative technique and recursive one. The accuracy of the methods depends on SNR levels, more specifically on the inherent accuracy of the Yule-Walker and lattice filter methods for signal plus noise system. The estimated noise variance is used for the blind indentification of AR and ARMA systems. Finally, to demonstrate the effectiveness of the method proposed here many numerical results are presented.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e77-a_5_847/_p
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@ARTICLE{e77-a_5_847,
author={Takashi YAHAGI, Md.Kamrul HASAN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Estimation of Noise Variance from Noisy Measurements of AR and ARMA Systems: Application to Blind Identification of Linear Time-Invariant Systems},
year={1994},
volume={E77-A},
number={5},
pages={847-855},
abstract={In many applications involving the processing of noisy signals, it is desired to know the noise variance. This paper proposes a new method for estimating the noise variance from the signals of autoregressive (AR) and autoregressive moving-average (ARMA) systems corrupted by additive white noise. The method proposed here uses the low-order Yule-Walker (LOYW) equations and the lattice filter (LF) algorithm for the estimation of noise variance from the noisy output measurements of AR and ARMA systems, respectively. Two techniques are proposed here: iterative technique and recursive one. The accuracy of the methods depends on SNR levels, more specifically on the inherent accuracy of the Yule-Walker and lattice filter methods for signal plus noise system. The estimated noise variance is used for the blind indentification of AR and ARMA systems. Finally, to demonstrate the effectiveness of the method proposed here many numerical results are presented.},
keywords={},
doi={},
ISSN={},
month={May},}
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TY - JOUR
TI - Estimation of Noise Variance from Noisy Measurements of AR and ARMA Systems: Application to Blind Identification of Linear Time-Invariant Systems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 847
EP - 855
AU - Takashi YAHAGI
AU - Md.Kamrul HASAN
PY - 1994
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E77-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 1994
AB - In many applications involving the processing of noisy signals, it is desired to know the noise variance. This paper proposes a new method for estimating the noise variance from the signals of autoregressive (AR) and autoregressive moving-average (ARMA) systems corrupted by additive white noise. The method proposed here uses the low-order Yule-Walker (LOYW) equations and the lattice filter (LF) algorithm for the estimation of noise variance from the noisy output measurements of AR and ARMA systems, respectively. Two techniques are proposed here: iterative technique and recursive one. The accuracy of the methods depends on SNR levels, more specifically on the inherent accuracy of the Yule-Walker and lattice filter methods for signal plus noise system. The estimated noise variance is used for the blind indentification of AR and ARMA systems. Finally, to demonstrate the effectiveness of the method proposed here many numerical results are presented.
ER -
English
