Hotrakool, W. and Abhayaratne, C. orcid.org/0000-0002-2799-7395 (2014) Fast compressed sensing reconstruction using the least squares and signal correlation. In: IET Intelligent Signal Processing Conference 2013 (ISP 2013). Proceedings of IET Intelligent Signal Processing Conference 2013 (ISP 2013), 02-03 Dec 2013, London, UK. The Institution of Engineering and Technology ISBN 9781849197748
Abstract
A fast compressed sensing reconstruction using least squares method with the signal correlation is presented in this paper. It is well known that the complexity of l 1 -minimisation is very high and is undesirable for many practical applications. The least squares method, on the other hand, has a much lower complexity. However, least squares does not promote the sparsity of signal and therefore cannot provide acceptable reconstructed results. The main contribution of this paper is to show that by exploiting signal correlation, the reconstruction error of least squares is greatly improved. Moreover, the correlated reference used in this method is very flexible, and can contain many kinds of correlation, such as spatial or temporal correlation. Experimental results show that the performance of this method is comparable to the state-of-the-art algorithms, whilst having a much lower complexity. It also shows that this method can be applied to both sparse and redundant signal reconstruction.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Institution of Engineering and Technology 2021. This is an author-produced version of a paper subsequently published in Proceedings of IET Intelligent Signal Processing Conference 2013 (ISP 2013). Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | least squares approximations; compressed sensing; correlation methods; signal reconstruction; minimisation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Oct 2021 12:54 |
Last Modified: | 01 Nov 2021 07:38 |
Status: | Published |
Publisher: | The Institution of Engineering and Technology |
Refereed: | Yes |
Identification Number: | 10.1049/cp.2013.2039 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:179777 |