Restricted Isometry Property of Principal Component Pursuit with Reduced Linear Measurements
نویسندگان
چکیده
منابع مشابه
Restricted Isometry Property of Principal Component Pursuit with Reduced Linear Measurements
The principal component prsuit with reduced linear measurements (PCP RLM) has gained great attention in applications, such as machine learning, video, and aligningmultiple images.The recent research shows that strongly convex optimization for compressive principal component pursuit can guarantee the exact low-rank matrix recovery and sparse matrix recovery as well. In this paper, we prove that ...
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This paper is concerned with the performance of Orthogonal Matching Pursuit (OMP) algorithms applied to a dictionary D in a Hilbert space H. Given an element f ∈ H, OMP generates a sequence of approximations fn, n = 1, 2, . . ., each of which is a linear combination of n dictionary elements chosen by a greedy criterion. It is studied whether the approximations fn are in some sense comparable to...
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ژورنال
عنوان ژورنال: Journal of Applied Mathematics
سال: 2013
ISSN: 1110-757X,1687-0042
DOI: 10.1155/2013/959403