Journal article
Parametrized quasi-soft thresholding operator for compressed sensing and matrix completion
Computational & applied mathematics, v 39(3)
22 May 2020
Abstract
Compressed sensing and matrix completion are two new approaches to signal acquisition and processing. Even though the two approaches are different, there is a close connection between them. We introduce a parametrized quasi-soft thresholding operator and use it to obtain new algorithms for compressed sensing and matrix completion. Furthermore, by updating the parametrized quasi-soft thresholding operator in every iteration, the varied parametric quasi-soft thresholding algorithm is obtained. The convergence of the algorithms is analyzed, and numerical results show that the new algorithms can effectively improve the accuracy.
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Details
- Title
- Parametrized quasi-soft thresholding operator for compressed sensing and matrix completion
- Creators
- Dongxiu Xie - Hunan UniversityHugo J. Woerdeman - Drexel UniversityAn-Bao Xu - Wenzhou University
- Publication Details
- Computational & applied mathematics, v 39(3)
- Publisher
- Springer Nature
- Number of pages
- 24
- Grant note
- 201406130046 / China Scholarship Council
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Mathematics
- Web of Science ID
- WOS:000536914900001
- Scopus ID
- 2-s2.0-85085342548
- Other Identifier
- 991019168569204721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Mathematics, Applied