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Dissipativity analysis and stabilization for discontinuous delayed complex-valued networks via matrix measure method

Overview of attention for article published in Advances in Continuous and Discrete Models, September 2018
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About this Attention Score

  • Among the highest-scoring outputs from this source (#46 of 189)

Mentioned by

peer_reviews
1 peer review site

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
3 Mendeley
Title
Dissipativity analysis and stabilization for discontinuous delayed complex-valued networks via matrix measure method
Published in
Advances in Continuous and Discrete Models, September 2018
DOI 10.1186/s13662-018-1786-5
Authors

Zengyun Wang, Jinde Cao, Zhenyuan Guo

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 > Doctoral Student 1 33%
Student > Master 1 33%
Readers by discipline Count As %
Mathematics 1 33%
Social Sciences 1 33%
Engineering 1 33%
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 02 September 2018.
All research outputs
#17,292,294
of 25,385,509 outputs
Outputs from Advances in Continuous and Discrete Models
#46
of 189 outputs
Outputs of similar age
#225,181
of 350,625 outputs
Outputs of similar age from Advances in Continuous and Discrete Models
#2
of 3 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 189 research outputs from this source. They receive a mean Attention Score of 1.6. This one has gotten more attention than average, scoring higher than 51% of its peers.
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 350,625 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.