LMS algorithm for unbiased parameter estimation of noisy autoregressive signals

H. C. So

doi:10.1049/el:20010325

Author(s)

H. C. So

Related Research Unit(s)

Department of Electrical Engineering

Detail(s)

Original language	English
Pages (from-to)	536-537
Journal / Publication	Electronics Letters
Volume	37
Issue number	8
Publication status	Published - 12 Apr 2001

Link(s)

DOI	DOI https://doi.org/10.1049/el:20010325 Final Published version
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Link to Scopus	https://www.scopus.com/record/display.uri?eid=2-s2.0-0035848724&origin=recordpage
Permanent Link	https://scholars.cityu.edu.hk/en/publications/publication(bcfa874f-4178-4b7c-88f8-e4aaccefe9f6).html

Abstract

A computationally simple algorithm is devised for unbiased autoregressive (AR) modelling in the presence of white noise, assuming that the power ratio of the AR driving source and the measurement noise is known. Convergence analysis of the proposed method is included and simulation results are presented to validate the theoretical derivations as well as to evaluate is estimation performance.

Citation Format(s)

[ RIS ] [ BibTeX ]

LMS algorithm for unbiased parameter estimation of noisy autoregressive signals. / So, H. C.

In: Electronics Letters, Vol. 37, No. 8, 12.04.2001, p. 536-537.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review

So, HC 2001, 'LMS algorithm for unbiased parameter estimation of noisy autoregressive signals', Electronics Letters, vol. 37, no. 8, pp. 536-537. https://doi.org/10.1049/el:20010325

So, H. C. (2001). LMS algorithm for unbiased parameter estimation of noisy autoregressive signals. Electronics Letters, 37(8), 536-537. https://doi.org/10.1049/el:20010325

So HC. LMS algorithm for unbiased parameter estimation of noisy autoregressive signals. Electronics Letters. 2001 Apr 12;37(8):536-537. doi: 10.1049/el:20010325

So, H. C. / LMS algorithm for unbiased parameter estimation of noisy autoregressive signals. In: Electronics Letters. 2001 ; Vol. 37, No. 8. pp. 536-537.