4.7 Review

Recursive Recovery of Sparse Signal Sequences From Compressive Measurements: A Review

期刊

IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 64, 期 13, 页码 3523-3549

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2016.2539138

关键词

Compressed sensing; sparse recovery; recursive reconstruction; compressive measurements

资金

  1. U.S. National Science Foundation (NSF) [CCF-0917015, CCF-1117125]
  2. Direct For Computer & Info Scie & Enginr
  3. Division of Computing and Communication Foundations [1526870] Funding Source: National Science Foundation
  4. Direct For Computer & Info Scie & Enginr
  5. Division of Computing and Communication Foundations [1117125] Funding Source: National Science Foundation

向作者/读者索取更多资源

In this overview article, we review the literature on design and analysis of recursive algorithms for reconstructing a time sequence of sparse signals from compressive measurements. The signals are assumed to be sparse in some transform domain or in some dictionary. Their sparsity patterns can change with time, although, in many practical applications, the changes are gradual. An important class of applications where this problem occurs is dynamic projection imaging, e.g., dynamic magnetic resonance imaging (MRI) for real-time medical applications such as interventional radiology, or dynamic computed tomography.

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