NDLI: Block-sparse signal recovery via ℓ2/ℓ1−2 minimisation method

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Volume 12 (2018) : Issue 3, May

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IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Block-sparse signal recovery via ℓ2/ℓ1−2 minimisation method

Content Provider	IET Digital Library
Author	Wang, Wendong Wang, Jianjun Zhang, Zili
Abstract	Motivated by the recently emerged ℓ 1 − 2 method for sparse signal recovery, in this study, the authors make an ongoing effect to extend this methodology to the setting of block sparsity, which directly leads to the proposed ℓ 2 / ℓ 1 − 2 method for block-sparse signal recovery. Some theoretical results are induced to guarantee the validity of proposed method. In particular, the obtained recovery condition rigorously includes the one induced by Yin et al., and the obtained error estimate can be used to model both the (block-) sparse and non-sparse signals, which is more comprehensive than that induced by Yin et al. which applies only to the sparse signals. The authors also derive an alternating direction method of multipliers (ADMM)-based algorithm to tackle the induced optimisation problem. Some experimental results that are based on the synthetic block-sparse signals and the real-world foetal electrocardiogram signals further demonstrate the better performance of the ℓ 2 / ℓ 1 − 2 method when it is compared with the state-of-the-art group-lasso method and ℓ 2 / ℓ q method for 0 < q < 1.
Starting Page	422
Ending Page	430
Page Count	9
ISSN	17519675
Volume Number	12
e-ISSN	17519683
Issue Number	Issue 4, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/12/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0381
Journal	IET Signal Processing
Publisher Date	2017-11-21
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ADMM-based Algorithm Bioelectric Signal Biology And Medical Computing Block-sparse Signal Recovery Digital Signal Processing Electrocardiography Electrodiagnostics And Other Electrical Measurement Technique Error Estimate Group-lasso Method Medical Signal Processing Minimisation Nonsparse Signal Optimisation Problem Optimisation Technique Real-world Foetal Electrocardiogram Signal Signal Processing And Detection Signal Restoration Synthetic Block-sparse Signal ℓ2-ℓ1-2 Minimisation Method
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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