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Statistical inference for block sparsity of complex signals
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. Department of Statistics, Zhejiang University City College, China.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. (Mathematical Statistics)ORCID-id: 0000-0001-5673-620x
2019 (engelsk)Manuskript (preprint) (Annet vitenskapelig)
Abstract [en]

Block sparsity is an important parameter in many algorithms to successfully recover block sparse signals under the framework of compressive sensing. However, it is often unknown and needs to beestimated. Recently there emerges a few research work about how to estimate block sparsity of real-valued signals, while there is, to the best of our knowledge, no investigation that has been conductedfor complex-valued signals. In this paper, we propose a new method to estimate the block sparsity of complex-valued signal. Its statistical properties are obtained and verified by simulations. In addition,we demonstrate the importance of accurately estimating the block sparsity in signal recovery through asensitivity analysis.

sted, utgiver, år, opplag, sider
2019.
Emneord [en]
Block sparsity, Complex-valued signals, Multivariate isotropic symmetric α-stable distribution
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Forskningsprogram
matematisk statistik
Identifikatorer
URN: urn:nbn:se:umu:diva-162998OAI: oai:DiVA.org:umu-162998DiVA, id: diva2:1348429
Ingår i projekt
Statistiska modeller och intelligenta datainsamlingsmetoder för MRI och PET mätningar med tillämpning för monitoring av cancerbehandling, Swedish Research CouncilTilgjengelig fra: 2019-09-04 Laget: 2019-09-04 Sist oppdatert: 2019-09-06

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arXiv September 2019

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Wang, JianfengZhou, ZhiyongYu, Jun

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