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Efficient Time-Recursive Implementation of Matched Filterbank Spectral Estimators
Centre for Digital Signal Processing Research, King’s College London, UK.
Karlstad University.
Royal Institute of Technology, Stockholm.ORCID iD: 0000-0002-7599-4367
2005 (English)In: IEEE Transactions on Circuits and Systems Part 1: Regular Papers, ISSN 1549-8328, Vol. 52, no 3, 516-521 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we present a computationally efficient sliding window time updating of the Capon and amplitude and phase estimation (APES) matched filterbank spectral estimators based on the time-variant displacement structure of the data covariance matrix. The presented algorithm forms a natural extension of the most computationally efficient algorithm to date, and offers a significant computational gain as compared to the computational complexity associated with the batch re-evaluation of the spectral estimates for each time-update. Furthermore, through simulations, the algorithm is found to be numerically superior to the time-updated spectral estimate formed from directly updating the data covariance matrix.

Place, publisher, year, edition, pages
2005. Vol. 52, no 3, 516-521 p.
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-77017DOI: 10.1109/TCSI.2004.842876OAI: diva2:524426
Available from: 2012-05-02 Created: 2012-05-02 Last updated: 2016-08-31Bibliographically approved

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Larsson, Erik G.
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ReferencesLink to record
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