A sparse optimization problem with hybrid L2-Lp regularization for application of magnetic resonance brain images

Regularization techniques have been proved useful in an enormous variety of sparse optimization problem. In this paper, we introduce a new formulation of regularization with a hybrid L 2 - L p ( 0 < p < 1 ) norm. Then we model a sparse optimization problem with hybrid L 2 - L p regularization....

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Veröffentlicht in:	Journal of combinatorial optimization 2021-11, Vol.42 (4), p.760-784
Hauptverfasser:	Gao, Xuerui, Bai, Yanqin, Li, Qian
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Brain Combinatorics Convex and Discrete Geometry Magnetic resonance imaging Mathematical Modeling and Industrial Mathematics Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Recovery Regularization Signal to noise ratio Theory of Computation
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