2016•AIP conference proceedingsRequires access

Optimization problems in structured low rank approximation

Jonathan Gillard, Dmitri E. Kvasov, Anatoly A. Zhigljavsky

Abstract

In this paper, we investigate the complexity of the numerical construction of the so-called Hankel structured low-rank approximation (HSLRA). Briefly, HSLRA is the problem of finding the closest (in some pre-defined norm) rank r approximation of a given Hankel matrix, which is also of Hankel structure.

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Key concepts: Hankel matrix, Low-rank approximation, Rank (graph theory), Matrix norm, Mathematics, Approximation algorithm, Computational complexity theory, Norm (philosophy)