Performance Analysis of Joint-Sparse Recovery from Multiple Measurement Vectors via Convex Optimization: Which Prior Information is Better?

Performance Analysis of Joint-Sparse Recovery from Multiple Measurement Vectors via Convex Optimization: Which Prior Information is Better?

In sparse signal recovery of compressive sensing, the phase transition determines the edge, which separates successful recovery and failed recovery. The phase transition can be seen as an indicator and an intuitive way to judge, which recovery performance is better. Traditionally, the multiple measu...

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Bibliographic Details
Main Authors:	Shih-Wei Hu, Gang-Xuan Lin, Sung-Hsien Hsieh, Chun-Shien Lu
Format:	Article
Language:	English
Published:	IEEE 2018-01-01
Series:	IEEE Access
Subjects:	Sparse representation <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">l</italic>₂,₁-norm minimization multiple-measurement vector statistical dimension compressed sensing convex optimization
Online Access:	https://ieeexplore.ieee.org/document/8253453/

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