caa a22 4500 606199446 CHVBK 20210128100938.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s11045-014-0282-7 doi (NATIONALLICENCE)springer-10.1007/s11045-014-0282-7 Split Bregman algorithms for sparse group Lasso with application to MRI reconstruction [Elektronische Daten] [Jian Zou, Yuli Fu] Sparse group lasso, concerning with group-wise and within-group sparsity, is generally considered difficult to solve due to the mixed-norm structure. In this paper, we propose efficient algorithms based on split Bregman iteration to solve sparse group lasso problems, including a synthesis prior form and an analysis prior form. These algorithms have low computational complexity and are suitable for large scale problems. The convergence of the proposed algorithms is also discussed. Moreover, the proposed algorithms are used for magnetic resonance imaging reconstruction. Numerical results show the effectiveness of the proposed algorithms. Springer Science+Business Media New York, 2014 Sparse group lasso nationallicence Split Bregman iteration nationallicence Convergence nationallicence MRI reconstruction nationallicence Zou Jian School of Information and Mathematics, Yangtze University, 434020, Jingzhou, Hubei, China aut Fu Yuli School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, Guangdong, China aut Multidimensional Systems and Signal Processing Springer US; http://www.springer-ny.com 26/3(2015-07-01), 787-802 0923-6082 26:3<787 2015 26 11045 https://doi.org/10.1007/s11045-014-0282-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11045-014-0282-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zou Jian School of Information and Mathematics, Yangtze University, 434020, Jingzhou, Hubei, China aut NATIONALLICENCE 700 1- Fu Yuli School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, Guangdong, China aut NATIONALLICENCE 773 0- Multidimensional Systems and Signal Processing Springer US; http://www.springer-ny.com 26/3(2015-07-01), 787-802 0923-6082 26:3<787 2015 26 11045