Affine projection subspace tracking
Document typeConference lecture
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
In this paper, we consider the problem of estimating and tracking an R-dimensional subspace with relevant information embedded in an N-dimensional ambient space, given that N>>R. We focus on a formulation of the signal subspace that interprets the problem as a least squares optimization. The approach we present relies on the geometrical concepts behind the Affine Projection Algorithms (APA) family to obtain the Affine Projection Subspace Tracking (APST) algorithm. This on-line solution possesses various desirable tracking capabilities, in addition to a high degree of configurability, making it suitable for a large range of applications with different convergence speed and computational complexity requirements. The APST provides a unified framework that generalises other well-known techniques, such as Oja’s rule and stochastic gradient based methods for subspace tracking. This algorithm is finally tested in a few synthetic scenarios against other classical adaptive methods.
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CitationVila, M.; Lopez, C.; Riba, J. Affine projection subspace tracking. A: IEEE International Conference on Acoustics, Speech, and Signal Processing. "ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)". Institute of Electrical and Electronics Engineers (IEEE), 2021, p. 3705-3709. ISBN 978-1-7281-7605-5. DOI 10.1109/ICASSP39728.2021.9415032.
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- Doctorat en Teoria del Senyal i Comunicacions - Ponències/Comunicacions de congressos 
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