Matrix completion concerns the recovery of a low-rank matrix from a subset of its revealedentries, and nuclear norm minimization has emerged as an effective surrogate for this combina-torial problem. Here, we show that nuclear norm minimization can recover an arbitrary n × nmatrix of rank r from O(nr log(n)) revealed entries, provided that revealed entries are drawnproportio...

Recovering a large matrix from limited measurements is a challenging task arising in many real applications, such as image inpainting, compressive sensing and medical imaging, and this kind of problems are mostly formulated as low-rank matrix approximation problems. Due to the rank operator being non-convex and discontinuous, most of the recent theoretical studies use the nuclear norm as a conv...

Matrix completion concerns the recovery of a low-rank matrix from a subset of its revealed entries, and nuclear norm minimization has emerged as an effective surrogate for this combinatorial problem. Here, we show that nuclear norm minimization can recover an arbitrary n⇥n matrix of rank r from O(nr log2(n)) revealed entries, provided that revealed entries are drawn proportionally to the local ...

Abstract Low-rank matrix recovery problem is difficult due to its non-convex properties and it usually solved using convex relaxation approaches. In this paper, we formulate the low-rank exactly novel Ky Fan 2- k -norm-based models. A general difference of functions algorithm (DCA) developed solve these proximal point (PPA) framework proposed sub-problems within DCA, which allows us handle larg...

In this paper, we compute H?-norm of a transfer matrix, via bisection algorithm. The algorithm is given and applied some problems. problems are choosen from various areas control theory such as aircraft models decentralized interconnected systems.

In the present paper, we give upper and lower bounds for the spectral norm of g-circulant matrix, whose the rst row entries are the classical Horadam numbers U (a,b) i . In addition, we also establish an explicit formula of the spectral norm for g-circulant matrix with the rst row ([U (a,b) 0 ] , [U (a,b) 1 ] , · · · , [U (a,b) n−1 ]).