Next Article in Journal
Stability Analysis and Synchronization for a Class of Fractional-Order Neural Networks
Previous Article in Journal
Sensitivity Analysis of Entropy Generation in Nanofluid Flow inside a Channel by Response Surface Methodology
Article Menu

Export Article

Open AccessArticle
Entropy 2016, 18(2), 53; doi:10.3390/e18020053

Bounding Extremal Degrees of Edge-Independent Random Graphs Using Relative Entropy

Department of Mathematics, Tongji University, Shanghai 200092, China
Academic Editor: J. A. Tenreiro Machado
Received: 2 December 2015 / Revised: 1 February 2016 / Accepted: 1 February 2016 / Published: 5 February 2016
(This article belongs to the Section Complexity)
View Full-Text   |   Download PDF [256 KB, uploaded 5 February 2016]   |  

Abstract

Edge-independent random graphs are a model of random graphs in which each potential edge appears independently with an individual probability. Based on the relative entropy method, we determine the upper and lower bounds for the extremal vertex degrees using the edge probability matrix and its largest eigenvalue. Moreover, an application to random graphs with given expected degree sequences is presented. View Full-Text
Keywords: extremal degree; relative entropy; edge-independent random graph extremal degree; relative entropy; edge-independent random graph
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Shang, Y. Bounding Extremal Degrees of Edge-Independent Random Graphs Using Relative Entropy. Entropy 2016, 18, 53.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top