Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices
نویسندگان
چکیده
منابع مشابه
Sparse and Low Rank Recovery
Compressive sensing (sparse recovery) is a new area in mathematical image and signal processing that predicts that sparse signals can be recovered from what was previously believed to be highly incomplete measurement [3, 5, 7, 12]. Recently, the ideas of this field have been extended to the recovery of low rank matrices from undersampled information [6, 8]; most notably to the matrix completion...
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2014
ISSN: 0018-9448,1557-9654
DOI: 10.1109/tit.2013.2288639