caa a22 4500 606199292 CHVBK 20210128100937.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s11045-013-0251-6 doi (NATIONALLICENCE)springer-10.1007/s11045-013-0251-6 Split Bregman algorithms for multiple measurement vector problem [Elektronische Daten] [Jian Zou, Yuli Fu, Qiheng Zhang, Haifeng Li] The standard sparse representation aims to reconstruct sparse signal from single measurement vector which is known as SMV model. In some applications, the SMV model extend to the multiple measurement vector (MMV) model, in which the signal consists of a set of jointly sparse vectors. In this paper, efficient algorithms based on split Bregman iteration are proposed to solve the MMV problems with both constrained form and unconstrained form. The convergence of the proposed algorithms is also discussed. Moreover, the proposed algorithms are used in magnetic resonance imaging reconstruction. Numerical results show the effectiveness of the proposed algorithms. Springer Science+Business Media New York, 2013 Multiple measurement vector problem 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 Zhang Qiheng School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, Guangdong, China aut Li Haifeng 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 26/1(2015-01-01), 207-224 0923-6082 26:1<207 2015 26 11045 https://doi.org/10.1007/s11045-013-0251-6 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/s11045-013-0251-6 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 700 1- Zhang Qiheng School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, Guangdong, China aut NATIONALLICENCE 700 1- Li Haifeng 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 26/1(2015-01-01), 207-224 0923-6082 26:1<207 2015 26 11045