In this paper, we investigate the complexity of the numerical construction of the Hankel structured low-rankudapproximation (HSLRA) problem, and develop a family of algorithms to solve this problem. Briefly, HSLRA is the problemudof finding the closest (in some pre-defined norm) rank r approximation of a given Hankel matrix, which is also of Hankeludstructure. Unlike many other methods described in the literature the family of algorithms we propose has the property ofudguaranteed convergence.
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