YAST Algorithm for Minor Subspace Tracking
Abstract
This paper introduces a new algorithm for tracking the minor subspace of the correlation matrix associated with time series. This algorithm is shown to have a better convergence rate than existing methods. Moreover, it guarantees the orthonormality of the subspace weighting matrix at each iteration, and reaches a linear complexity.
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