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Sparse Analysis Recovery via Iterative Cosupport Detection Estimation
- Source :
- IEEE Access, Vol 9, Pp 38386-38395 (2021)
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- Cosparse analysis model (CAM) provides a new signal processing paradigm for recovering cosparse signals with respect to a given analysis operator from the undersampled linear measurements in the context of emerging theory of compressed sensing (CS). The sparse analysis recovery/cosparse recovery is a key one brought up by this new paradigm. In this paper, we propose a new family of analysis pursuit algorithms for the sparse analysis recovery problem when the signals obey the cosparse analysis model, termed as iterative cosupport detection estimation (ICDE). ICDE is an algorithmic framework, which alternates between detecting a cosupport set of the unknown true signal and estimating the underlying signal by solving a truncated analysis pursuit problem on the detected cosupport. Further, we propose effective implementations of ICDE equipped with an efficient thresholding strategy for cosupport detection. Empirical performance comparisons show that ICDE is favorable in comparison with the state-of-the-art sparse analysis recovery algorithms. Source code of ICDE has been made publicly available on Github: https://github.com/songhp/ICDE. Beijing Natural Science Foundation (BNSF) under Grant No. 4194076, the Natural Science Foundation of Jiangsu Province under Grant No. BK20170558 and the China Scholarship Council (CSC, No. 202008320094).
- Subjects :
- Source code
General Computer Science
Computer science
media_common.quotation_subject
Context (language use)
02 engineering and technology
Set (abstract data type)
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
Sparse representation
cosparse analysis model
compressed sensing
Sparse matrix
media_common
Signal processing
General Engineering
020206 networking & telecommunications
Sparse approximation
Thresholding
Compressed sensing
020201 artificial intelligence & image processing
lcsh:Electrical engineering. Electronics. Nuclear engineering
lcsh:TK1-9971
Algorithm
sparse signal processing
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....11343dea1a633a7591e6d267fae7d5b7