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	A Fast Linearized Alternating Minimization Algorithm for Constrained High-Order Total Variation Regularized Compressive Sensing
	Hao B.; Wang J.; Zhu J.
刊名	IEEE Access
	2019
卷号	7页码:143081-143089
关键词	alternating direction method Compressive sensing image reconstruction second-order total variation
DOI	10.1109/ACCESS.2019.2944173
URL标识	查看原文
公开日期	[db:dc_date_available]
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/4558181
专题	山东大学
作者单位	1.College of Science, China University of Petroleum, Qingdao, 266580, China 2.College of Science, China University of Petroleum, Qingd
推荐引用方式 GB/T 7714	Hao B.,Wang J.,Zhu J.. A Fast Linearized Alternating Minimization Algorithm for Constrained High-Order Total Variation Regularized Compressive Sensing[J]. IEEE Access,2019,7:143081-143089.
APA	Hao B.,Wang J.,&Zhu J..(2019).A Fast Linearized Alternating Minimization Algorithm for Constrained High-Order Total Variation Regularized Compressive Sensing.IEEE Access,7,143081-143089.
MLA	Hao B.,et al."A Fast Linearized Alternating Minimization Algorithm for Constrained High-Order Total Variation Regularized Compressive Sensing".IEEE Access 7(2019):143081-143089.

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