Revising regularisation with linear approximation term for compressive sensing improvement

Chen, Zan, Hou, Xingsong, Shao, Ling and Wang, Shidong (2019) Revising regularisation with linear approximation term for compressive sensing improvement. Electronics Letters, 55 (7). pp. 384-386. ISSN 0013-5194

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Abstract

In this Letter, the authors propose a novel revised regularisation to improve the performance of compressive sensing (CS) reconstruction. They suppose that a specific regularisation term is insufficient to accommodate the prior information of CS while it can be improved by further imposing a linear approximation term. They also prove that the revised regularisation is substantially equivalent to the CS preprocessing methods. They conduct extensive experiments on various CS algorithms, which show the effectiveness of their revised regularisation.

Item Type: Article
Uncontrolled Keywords: electrical and electronic engineering ,/dk/atira/pure/subjectarea/asjc/2200/2208
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 08 May 2019 15:30
Last Modified: 10 Nov 2020 01:07
URI: https://ueaeprints.uea.ac.uk/id/eprint/70872
DOI: 10.1049/el.2018.8019

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