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Fast sparsity adaptive matching pursuit algorithm for large-scale image reconstruction

Overview of attention for article published in EURASIP Journal on Wireless Communications and Networking, April 2018
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Mentioned by

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1 X user

Citations

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Readers on

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3 Mendeley
Title
Fast sparsity adaptive matching pursuit algorithm for large-scale image reconstruction
Published in
EURASIP Journal on Wireless Communications and Networking, April 2018
DOI 10.1186/s13638-018-1085-6
Authors

Shihong Yao, Qingfeng Guan, Sheng Wang, Xiao Xie

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Student > Master 1 33%
Unknown 1 33%
Readers by discipline Count As %
Engineering 1 33%
Unknown 2 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 April 2018.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from EURASIP Journal on Wireless Communications and Networking
#363
of 549 outputs
Outputs of similar age
#267,928
of 343,278 outputs
Outputs of similar age from EURASIP Journal on Wireless Communications and Networking
#14
of 17 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 549 research outputs from this source. They receive a mean Attention Score of 2.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 343,278 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.