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Proceedings Paper

Adaptive rational subspace estimation: case of nonwhite additive noise
Author(s): Inbar Fijalkow; Philippe Loubaton
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Paper Abstract

In previous work, time domain algorithms were proposed to adaptively estimate a rational and orthonormal spanning of rational source and noise subspaces using a cascadable lossless structure. However, they apply only if the additive channel noise occurring at the receiver sensor array is a spatially and temporally white multivariate process. We propose a new approach in the case where the `useful' signal is corrupted by an additive spatially and/or temporally non-white noise. The source and noise subspaces are characterized by the mean of fourth order statistics under pragmatic assumptions on the sources and noise distributions. A new adaptive algorithm is deduced and its satisfactory asymptotical convergence properties are proved.

Paper Details

Date Published: 28 October 1994
PDF: 12 pages
Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); doi: 10.1117/12.190834
Show Author Affiliations
Inbar Fijalkow, Cornell Univ. (United States)
Philippe Loubaton, Telecom Paris (France)


Published in SPIE Proceedings Vol. 2296:
Advanced Signal Processing: Algorithms, Architectures, and Implementations V
Franklin T. Luk, Editor(s)

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