Sökning: id:"swepub:oai:DiVA.org:umu-152530" >
Sparse recovery bas...
Sparse recovery based on q-ratio constrained minimal singular values
-
- Zhou, Zhiyong (författare)
- Umeå universitet,Institutionen för matematik och matematisk statistik
-
- Yu, Jun, 1962- (författare)
- Umeå universitet,Institutionen för matematik och matematisk statistik,Mathematical Statistics
-
(creator_code:org_t)
- Elsevier, 2019
- 2019
- Engelska.
-
Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 155, s. 247-258
- Relaterad länk:
-
http://arxiv.org/pdf...
-
visa fler...
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- We study verifiable sufficient conditions and computable performance bounds for sparse recovery algorithms such as the Basis Pursuit, the Dantzig selector and the Lasso estimator, in terms of a newly defined family of quality measures for the measurement matrices. With high probability, the developed measures for subgaussian random matrices are bounded away from zero as long as the number of measurements is reasonably large. Comparing to the restricted isotropic constant based performance analysis, the arguments in this paper are much more concise and the obtained bounds are tighter. Numerical experiments are presented to illustrate our theoretical results.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Compressive sensing
- q-ratio sparsity
- q-ratio constrained minimal singular values
- Convex–concave procedure
- matematisk statistik
- Mathematical Statistics
- Signal Processing
- signalbehandling
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas