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Article . 2019 . Peer-reviewed
License: Elsevier TDM
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Compressive sensing reconstruction for vibration signals based on the improved fast iterative shrinkage-thresholding algorithm

Authors: Qiang Wang; Chen Meng; Weining Ma; Cheng Wang; Lei Yu;

Compressive sensing reconstruction for vibration signals based on the improved fast iterative shrinkage-thresholding algorithm

Abstract

Abstract We consider the compressive sensing reconstruction for vibration signals, which are complex due to the harsh working environment. The recent fast iterative shrinkage-thresholding algorithm (FISTA) has paved the way for the signal reconstruction with a low complexity and high efficiency. Unfortunately, when extending to the vibration signals, the current algorithm still has some drawbacks such as the bad reconstruction effect. In this paper, we propose the improved fast iterative shrinkage-thresholding algorithm (IFISTA) to improve the reconstruction effect. Under the new scheme, the reconstruction is promoted by extracting information from the unstable signals in the process of iteration. Then the feature coefficients will be protected from shrinkage during iteration. The effectiveness of the IFISTA is verified by simulated signals and acquired signals. It is showed that the proposed scheme has superior performance in reconstruction and feature protection for vibration signals.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Top 10%
Top 10%
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