JOURNAL ARTICLE
Gradient dynamical systems for principal singular subspace analysis
Abstract
Principal singular component analysis has recently been proposed and analyzed by the author. It is a generalization of the principal singular subspace analysis which has been investigated in the literature. In this paper an unconstrained weighted cost function is utilized to develop dynamical systems that converge to the actual principal singular vectors of a given matrix. Stability analysis that reveals the domains of attraction of these systems is also given.
Keywords:
Subspace topology Principal component analysis Generalization Singular value Principal (computer security) Stability (learning theory) Mathematics Applied mathematics Dynamical systems theory Singular solution Matrix (chemical analysis) Function (biology) Computer science Mathematical optimization Mathematical analysis Artificial intelligence Eigenvalues and eigenvectors Physics Machine learning
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3
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0.67
FWCI (Field Weighted Citation Impact)
13
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0.73
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Citation History
Topics
Blind Source Separation Techniques
Physical Sciences → Computer Science → Signal Processing
Matrix Theory and Algorithms
Physical Sciences → Computer Science → Computational Theory and Mathematics
Scientific Research and Discoveries
Physical Sciences → Physics and Astronomy → Statistical and Nonlinear Physics
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