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Bounds for degree-based network entropies

Author

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  • Chen, Zengqiang
  • Dehmer, Matthias
  • Shi, Yongtang

Abstract

In this paper, we continue studying degree-based entropies for networks. The quantities represent information-theoretic network measures which are based on using information functionals involving vertex degrees. We prove bounds for entropies which are based on information functionals using degree powers and come up with interrelations between different measures. Such interrelations are important to study connections between the measures required to understand the measures in depth.

Suggested Citation

  • Chen, Zengqiang & Dehmer, Matthias & Shi, Yongtang, 2015. "Bounds for degree-based network entropies," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 983-993.
    • Handle: RePEc:eee:apmaco:v:265:y:2015:i:c:p:983-993
    DOI: 10.1016/j.amc.2015.06.003
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    References listed on IDEAS

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    1. Cao, Shujuan & Dehmer, Matthias, 2015. "Degree-based entropies of networks revisited," Applied Mathematics and Computation, Elsevier, vol. 261(C), pages 141-147.
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    Cited by:

    1. Cao, Shujuan & Dehmer, Matthias & Kang, Zhe, 2017. "Network Entropies Based on Independent Sets and Matchings," Applied Mathematics and Computation, Elsevier, vol. 307(C), pages 265-270.
    2. Agryzkov, Taras & Tortosa, Leandro & Vicent, Jose F., 2016. "New highlights and a new centrality measure based on the Adapted PageRank Algorithm for urban networks," Applied Mathematics and Computation, Elsevier, vol. 291(C), pages 14-29.
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    4. Yu, Guihai & Qu, Hui, 2015. "Hermitian Laplacian matrix and positive of mixed graphs," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 70-76.
    5. Xing Zhou & Wei Peng & Zhen Xu & Bo Yang, 2015. "Hardness Analysis and Empirical Studies of the Relations among Robustness, Topology and Flow in Dynamic Networks," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-29, December.

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