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J. Zou, Y. Fu, Q. Zhang and H. Li., Split Bregman algorithms for multiple measurement vector problem, Multidimensional Systems and Signal Processing, vol. 26, pp. 207-224, 2015.
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Split Bregman algorithms for multiple measurement vector problem
作者:Zou, J (Zou, Jian)[ 2,1 ] ; Fu, YL (Fu, Yuli)[ 2 ] ; Zhang, QH (Zhang, Qiheng)[ 2 ] ; Li, HF (Li, Haifeng)[ 2 ]
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING
卷: 26 期: 1 頁: 207-224
DOI: 10.1007/s11045-013-0251-6
出版年: JAN 2015
查看期刊信息
摘要
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.
關(guān)鍵詞
作者關(guān)鍵詞:Multiple measurement vector problem; Split Bregman iteration; Convergence; MRI reconstruction
KeyWords Plus:SIMULTANEOUS SPARSE APPROXIMATION; RANK AWARENESS; MR-IMAGES; RECONSTRUCTION; RECOVERY
作者信息
通訊作者地址: Fu, YL (通訊作者)
顯示增強(qiáng)組織信息的名稱 S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China.
地址:
[ 1 ] Yangtze Univ, Sch Informat & Math, Jinzhou 434020, Hubei, Peoples R China
顯示增強(qiáng)組織信息的名稱 [ 2 ] S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China
電子郵件地址:zoujianjz@gmail.com; fuyuli@scut.edu.cn; qiheng.zhang@gmail.com; lihaifengxx@126.com
基金資助致謝
基金資助機(jī)構(gòu) 授權(quán)號(hào)
International cooperation project of Guangdong Natural Science Foundation
2009B050700020
NSFC-Guangdong Union Project
U0835003
NSFC
60903170
61004054
61104053
61103122
查看基金資助信息
出版商
SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
類別 / 分類
研究方向:Computer Science; Engineering
Web of Science 類別:Computer Science, Theory & Methods; Engineering, Electrical & Electronic
文獻(xiàn)信息
文獻(xiàn)類型:Article
語種:English
入藏號(hào): WOS:000347953000012
ISSN: 0923-6082
eISSN: 1573-0824
其他信息
IDS 號(hào): AZ0RT
Web of Science 核心合集中的 "引用的參考文獻(xiàn)": 33
Web of Science 核心合集中的 "被引頻次": 0

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