OptShrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage

25 Jun 2013Raj Rao Nadakuditi

The truncated singular value decomposition (SVD) of the measurement matrix is the optimal solution to the_representation_ problem of how to best approximate a noisy measurement matrix using a low-rank matrix. Here, we consider the (unobservable)_denoising_ problem of how to best approximate a low-rank signal matrix buried in noise by optimal (re)weighting of the singular vectors of the measurement matrix... (read more)

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