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Estimation of block sparsity in compressive sensing
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. (Mathematical Statistics)
2017 (English)Manuscript (preprint) (Other academic)
Abstract [en]

In this paper, we consider a soft measure of block sparsity, k_α(x)=(∥x∥2,α/∥x∥2,1)^α/(1−α),α∈[0,∞] and propose a procedure to estimate it by using multivariate isotropic symmetric α-stable random projections without sparsity or block sparsity assumptions. The limiting distribution of the estimator is given. Some simulations are conducted to illustrate our theoretical results.

Place, publisher, year, edition, pages
2017. , p. 15
Keywords [en]
Block sparsity; Multivariate isotropic symmetric alpha-stable distribution; Compressive sensing; Characteristic function
National Category
Probability Theory and Statistics Computational Mathematics Medical Image Processing
Research subject
Mathematical Statistics
Identifiers
URN: urn:nbn:se:umu:diva-141542OAI: oai:DiVA.org:umu-141542DiVA, id: diva2:1155305
Projects
Statistical modelling and intelligent data sampling in MRI and PET measurements for cancer therapy assessment
Funder
Swedish Research Council, 340-2013-5342Available from: 2017-11-07 Created: 2017-11-07 Last updated: 2018-06-09

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arXiv:1701.01055

Authority records BETA

Zhou, ZhiyongYu, Jun

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CiteExportLink to record
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Citation style
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