Title
Author
Year
Volume
:
2024
Vol. 1
no. 1
Vol. 2
2023
Vol. 1
no. 1
no. 2
2022
Vol. 1
no. 1
2021
Vol. 1
no. 1
2019
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no. 1
no. 2
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no. 1
Vol. 2
no. 1
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Vol. 1
no. 1
Vol. 2
no. 1
2010
Vol. 1
no. 1
no. 2
Vol. 2
Vol. 0
Vol. 1
A Joint Iterative Estimation of Noise Variance and AR Parameters
Pages
:
1-6
Jonah Gam , Tetsuya Shimamura , Shuji Kawasaki , Masakazu Higuchi, Hitomi Murakami
The problem of determining autoregressive (AR) parameters fromobservations corrupted by stationary white Gaussian noise without a prioriknowledge of the noise variance is addressed. We propose a new approachin which the noise variance and AR parameters are jointly and iterativelyestimated from low-order Yule-Walker equations. This approachavoids using unreliable high-order Yule-Walker equations (HOYWEs) orover-determined Yule-Walker equations (ODYWEs). For short observations,noise-compensated data extrapolation (NCDE) is employed. Simulationresults demonstrate the e?ectiveness of the proposed approach.
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