NDLI: Robust recursive spectral estimation based on AR model excited by a t-distribution process

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Robust recursive spectral estimation based on AR model excited by a t-distribution process

Content Provider	IEEE Xplore Digital Library
Author	Sanubari, J. Tokuda, K. Onoda, M.
Copyright Year	1994
Description	Author affiliation: Dept. of Electron. Eng., Satya Wacana Univ., Salatiga, Indonesia (Sanubari, J.)
Abstract	In this paper a new robust spectral estimation method based on an AR model is proposed. The optimal coefficient is selected by assuming that the excitation signal is t-distribution t(/spl alpha/) with /spl alpha/ degrees of freedom. The calculation is done by using a recursive algorithm. When /spl alpha/=/spl infin/, we get the RLS method. Simulation results show that the obtained estimates using the proposed method with small /spl alpha/ are more efficient, the standard deviation (SD) of the estimation results are smaller, and more accurate than that with large /spl alpha/. The proposed estimator with small /spl alpha/ is more efficient and more accurate then the recursive method based on Huber's M-estimate.<>
File Size	307247
File Format	PDF
ISBN	0780317750
ISSN	15206149
DOI	10.1109/ICASSP.1994.389981
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-04-19
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Recursive estimation Equations Digital signal processing chips Probability density function Iterative methods Iterative algorithms Parameter estimation Random processes Transfer functions
Content Type	Text
Resource Type	Article

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