Generalized Degree-Based Graph Entropies

被引：1
|
作者：
Lu, Guoxiang [1 ]
机构：
[1] Zhongnan Univ Econ & Law, Sch Math & Stat, 182 Nanhu Ave, Wuhan 430073, Peoples R China
来源：
SYMMETRY-BASEL | 2017年 / 9卷 / 03期
关键词：
network; information theory; entropy measure; graph entropy; generalized degree-based graph entropy; degree powers; 1ST ZAGREB INDEX; COMPLEX NETWORKS; RANDIC INDEX; ESTRADA INDEX; TREES; ORDER; SMALLEST; ENERGY;
D O I：
10.3390/sym9030029
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Inspired by the generalized entropies for graphs, a class of generalized degree-based graph entropies is proposed using the known information-theoretic measures to characterize the structure of complex networks. The new entropies depend on assigning a probability distribution about the degrees to a network. In this paper, some extremal properties of the generalized degree-based graph entropies by using the degree powers are proved. Moreover, the relationships among the entropies are studied. Finally, numerical results are presented to illustrate the features of the new entropies.
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页数：13
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