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Entropy bounds for dendrimers

Tutkimustuotosvertaisarvioitu

Standard

Entropy bounds for dendrimers. / Chen, Zengqiang; Dehmer, Matthias; Emmert-Streib, Frank; Shi, Yongtang.

julkaisussa: Applied Mathematics and Computation, Vuosikerta 242, 01.09.2014, s. 462-472.

Tutkimustuotosvertaisarvioitu

Harvard

Chen, Z, Dehmer, M, Emmert-Streib, F & Shi, Y 2014, 'Entropy bounds for dendrimers', Applied Mathematics and Computation, Vuosikerta. 242, Sivut 462-472. https://doi.org/10.1016/j.amc.2014.05.105

APA

Chen, Z., Dehmer, M., Emmert-Streib, F., & Shi, Y. (2014). Entropy bounds for dendrimers. Applied Mathematics and Computation, 242, 462-472. https://doi.org/10.1016/j.amc.2014.05.105

Vancouver

Chen Z, Dehmer M, Emmert-Streib F, Shi Y. Entropy bounds for dendrimers. Applied Mathematics and Computation. 2014 syys 1;242:462-472. https://doi.org/10.1016/j.amc.2014.05.105

Author

Chen, Zengqiang ; Dehmer, Matthias ; Emmert-Streib, Frank ; Shi, Yongtang. / Entropy bounds for dendrimers. Julkaisussa: Applied Mathematics and Computation. 2014 ; Vuosikerta 242. Sivut 462-472.

Bibtex - Lataa

@article{616ec59eb2784086924bfa7aaa3adde1,
title = "Entropy bounds for dendrimers",
abstract = "Many graph invariants have been used for the construction of entropy-based measures to characterize the structure of complex networks. When considering Shannon entropy-based graph measures, there has been very little work to find their extremal values. A reason for this might be the fact that Shannon's entropy represents a multivariate function and all probability values are not equal to zero when considering graph entropies. Dehmer and Kraus proved some extremal results for graph entropies which are based on information functionals and express some conjectures generated by numerical simulations to find extremal values of graph entropies. Dehmer and Kraus discussed the extremal values of entropies for dendrimers. In this paper, we continue to study the extremal values of graph entropy for dendrimers, which has most interesting applications in molecular structure networks, and also in the pharmaceutical and biomedical area. Among all dendrimers with n vertices, we obtain the extremal values of graph entropy based on different well-known information functionals. Numerical experiments verifies our results.",
keywords = "Dendrimers, Extremal values, Graph entropy, Information theory, Shannon's entropy",
author = "Zengqiang Chen and Matthias Dehmer and Frank Emmert-Streib and Yongtang Shi",
year = "2014",
month = "9",
day = "1",
doi = "10.1016/j.amc.2014.05.105",
language = "English",
volume = "242",
pages = "462--472",
journal = "Applied Mathematics and Computation",
issn = "0096-3003",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Entropy bounds for dendrimers

AU - Chen, Zengqiang

AU - Dehmer, Matthias

AU - Emmert-Streib, Frank

AU - Shi, Yongtang

PY - 2014/9/1

Y1 - 2014/9/1

N2 - Many graph invariants have been used for the construction of entropy-based measures to characterize the structure of complex networks. When considering Shannon entropy-based graph measures, there has been very little work to find their extremal values. A reason for this might be the fact that Shannon's entropy represents a multivariate function and all probability values are not equal to zero when considering graph entropies. Dehmer and Kraus proved some extremal results for graph entropies which are based on information functionals and express some conjectures generated by numerical simulations to find extremal values of graph entropies. Dehmer and Kraus discussed the extremal values of entropies for dendrimers. In this paper, we continue to study the extremal values of graph entropy for dendrimers, which has most interesting applications in molecular structure networks, and also in the pharmaceutical and biomedical area. Among all dendrimers with n vertices, we obtain the extremal values of graph entropy based on different well-known information functionals. Numerical experiments verifies our results.

AB - Many graph invariants have been used for the construction of entropy-based measures to characterize the structure of complex networks. When considering Shannon entropy-based graph measures, there has been very little work to find their extremal values. A reason for this might be the fact that Shannon's entropy represents a multivariate function and all probability values are not equal to zero when considering graph entropies. Dehmer and Kraus proved some extremal results for graph entropies which are based on information functionals and express some conjectures generated by numerical simulations to find extremal values of graph entropies. Dehmer and Kraus discussed the extremal values of entropies for dendrimers. In this paper, we continue to study the extremal values of graph entropy for dendrimers, which has most interesting applications in molecular structure networks, and also in the pharmaceutical and biomedical area. Among all dendrimers with n vertices, we obtain the extremal values of graph entropy based on different well-known information functionals. Numerical experiments verifies our results.

KW - Dendrimers

KW - Extremal values

KW - Graph entropy

KW - Information theory

KW - Shannon's entropy

UR - http://www.scopus.com/inward/record.url?scp=84903150191&partnerID=8YFLogxK

U2 - 10.1016/j.amc.2014.05.105

DO - 10.1016/j.amc.2014.05.105

M3 - Article

VL - 242

SP - 462

EP - 472

JO - Applied Mathematics and Computation

JF - Applied Mathematics and Computation

SN - 0096-3003

ER -