A new iterative weighted norm minimization algorithm and its applications
作者： I.F. Gorodnitsky , B.D. Rao
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摘要: A general class of linear inverse problems in which the solutions are sparse and localized is considered. The proposed algorithm a nonparametric approach that finds without prior information on constraints. Each step iterative procedure consists solving weighted least squares problem wherein weighting matrix determined by solution from previous iteration. Some properties along with its applications to direction arrival spectrum estimation presented. >
sci-hub.se 参考文章(3)
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