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On-Line Singular Value Decomposition of Stochastic Process Covariances

Landelius, Tomas (author)
n/a
Knutsson, Hans (author)
Linköpings universitet,Bildbehandling,Tekniska högskolan
Borga, Magnus (author)
Linköpings universitet,Bildbehandling,Tekniska högskolan
 (creator_code:org_t)
Linköping, Sweden : Linköping University, Department of Electrical Engineering, 1995
English 6 s.
Series: LiTH-ISY-R, 1400-3902 ; 1762
  • Reports (other academic/artistic)
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  • This paper presents novel algorithms for finding the singular value decomposition (SVD) of a general covariance matrix by stochastic approximation. General in the sense that also non-square, between sets, covariance matrices are dealt with. For one of the algorithms, convergence is shown using results from stochastic approximation theory. Proofs of this sort, establishing both the point of equilibrium and its domain of attraction, have been reported very rarely for stochastic, iterative feature extraction algorithms.

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TECHNOLOGY
TEKNIKVETENSKAP

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rap (subject category)

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Landelius, Tomas
Knutsson, Hans
Borga, Magnus
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LiTH-ISY-R,
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Linköping University

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