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Robust Adaptive Recurrent Cerebellar Model Neural Network for Non-linear System Based on GPSO

Overview of attention for article published in Frontiers in Neuroscience, May 2019
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1 X user

Citations

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7 Dimensions

Readers on

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10 Mendeley
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Title
Robust Adaptive Recurrent Cerebellar Model Neural Network for Non-linear System Based on GPSO
Published in
Frontiers in Neuroscience, May 2019
DOI 10.3389/fnins.2019.00390
Pubmed ID
Authors

Jian-sheng Guan, Shao-jiang Hong, Shao-bo Kang, Yong Zeng, Yuan Sun, Chih-Min Lin

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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 20%
Student > Doctoral Student 1 10%
Lecturer 1 10%
Professor 1 10%
Professor > Associate Professor 1 10%
Other 0 0%
Unknown 4 40%
Readers by discipline Count As %
Engineering 3 30%
Computer Science 1 10%
Biochemistry, Genetics and Molecular Biology 1 10%
Neuroscience 1 10%
Medicine and Dentistry 1 10%
Other 0 0%
Unknown 3 30%
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 30 May 2019.
All research outputs
#23,416,163
of 26,086,865 outputs
Outputs from Frontiers in Neuroscience
#10,408
of 11,751 outputs
Outputs of similar age
#317,949
of 367,326 outputs
Outputs of similar age from Frontiers in Neuroscience
#292
of 323 outputs
Altmetric has tracked 26,086,865 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,751 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one is in the 1st percentile – i.e., 1% 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 367,326 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 323 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.