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Proceedings Paper

Noniterative subspace updating
Author(s): Ronald D. DeGroat; Eric M. Dowling
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Paper Abstract

In this paper, we introduce a rank-one spherical subspace update that is appropriate for tracking the dominant (signal) and/or subdominant (noise) subspaces associated with a slowly time-varying correlation matrix. This non-iterative, highly parallel, numerically stabilized, subspace update is closely related to rank-one eigenstructure updating. However, a rank-one subspace update involves less computation than simple rank-one correlation accumulation. Moreover, the frequency tracking capabilities of the non-iterative subspace update are virtually identical to and in some cases more robust than the more computationally expensive eigen- based methods.

Paper Details

Date Published: 1 December 1991
PDF: 12 pages
Proc. SPIE 1566, Advanced Signal Processing Algorithms, Architectures, and Implementations II, (1 December 1991); doi: 10.1117/12.49839
Show Author Affiliations
Ronald D. DeGroat, Univ. of Texas/Dallas (United States)
Eric M. Dowling, Univ. of Texas/Dallas (United States)

Published in SPIE Proceedings Vol. 1566:
Advanced Signal Processing Algorithms, Architectures, and Implementations II
Franklin T. Luk, Editor(s)

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