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Stability of weighted spectral distribution in a pseudo tree-like network model |
Bo Jiao(焦波)1, Yuan-ping Nie(聂原平)2, Cheng-dong Huang(黄赪东)1, Jing Du(杜静)1, Rong-hua Guo(郭荣华)1, Fei Huang(黄飞)1, Jian-mai Shi(石建迈)3 |
1. Luoyang Electronic Equipment Test Center, Luoyang 471003, China;
2. College of Computer, National University of Defense Technology, Changsha 410073, China;
3. College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China |
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Abstract The comparison of networks with different orders strongly depends on the stability analysis of graph features in evolving systems. In this paper, we rigorously investigate the stability of the weighted spectral distribution (i.e., a spectral graph feature) as the network order increases. First, we use deterministic scale-free networks generated by a pseudo tree-like model to derive the precise formula of the spectral feature, and then analyze the stability of the spectral feature based on the precise formula. Except for the scale-free feature, the pseudo tree-like model exhibits the hierarchical and small-world structures of complex networks. The stability analysis is useful for the classification of networks with different orders and the similarity analysis of networks that may belong to the same evolving system.
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Received: 23 September 2015
Revised: 26 December 2015
Accepted manuscript online:
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PACS:
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89.75.Hc
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(Networks and genealogical trees)
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05.40.Fb
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(Random walks and Levy flights)
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05.10.-a
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(Computational methods in statistical physics and nonlinear dynamics)
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Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61402485, 61303061, and 71201169). |
Corresponding Authors:
Bo Jiao
E-mail: jiaoboleetc@outlook.com
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Cite this article:
Bo Jiao(焦波), Yuan-ping Nie(聂原平), Cheng-dong Huang(黄赪东), Jing Du(杜静), Rong-hua Guo(郭荣华), Fei Huang(黄飞), Jian-mai Shi(石建迈) Stability of weighted spectral distribution in a pseudo tree-like network model 2016 Chin. Phys. B 25 058901
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[1] |
Leskovec 2015 J http://snap.stanford.edu/data/accessed Dec 2015
|
[2] |
Wu J, Barahona M, Tan Y J and Deng H Z 2010 Chin. Phys. Lett. 27 078902
|
[3] |
Wu J, Barahona M, Tan Y J and Deng H Z 2012 Chaos 22 043101
|
[4] |
Jiao B, Nie Y P, Shi J M, Lu G, Zhou Y and Du J 2015 Telecommun. Syst.
|
[5] |
Jiao B, Zhou Y, Du J, Huang C D, Lu Z Y and Liu Y L 2014 IET Commun. 8 2845
|
[6] |
Fay D, Haddadi H, Uhlig S, Kilmartin L, Moore A W, Kunegis J and Iliofotou M 2011 Comput. Network 55 3458
|
[7] |
Fay D, Haddadi H, Thomason A, Moore A W, Mortier R, Jamakovic A, Uhlig S and Rio M 2010 IEEE ACM T. Network 18 164
|
[8] |
Haddadi H, Fay D, Jamakovic A, Maennel O, Moore A W, Mortier R and Uhlig S 2009 21st International Teletraffic Congress (Paris: IEEE) pp. 1-8
|
[9] |
Jiao B and Shi J M 2015 Comput. Commun. 76 77
|
[10] |
Jing X L, Ling X, Hu M B and Shi Q 2014 Chin. Phys. Lett. 31 080504
|
[11] |
Li L, Guan J H and Zhou S G 2015 Chin. Phys. Lett. 32 030501
|
[12] |
Comellas F and Sampels M 2002 Physica A 309 231
|
[13] |
Zhang J Y, Sun W G and Chen G R 2012 Chin. Phys. B 21 038901
|
[14] |
Sun W G, Zhang J Y and Chen G R 2013 Chin. Phys. B 22 108904
|
[15] |
Sun Y, Dai M and Xi L 2014 Physica A 407 110
|
[16] |
Dai M, Chen D, Dong Y and Liu J 2012 Physica A 391 6165
|
[17] |
Comellas F and Miralles A 2010 Phys. Rev. E 81 061103
|
[18] |
Zhang Z, Yang Y and Lin Y 2012 Phys. Rev. E 85 011106
|
[19] |
Barabasi A L, Ravasz E and Vicsek T 2001 Physica A 299 559
|
[20] |
Chen M, Yu B, Xu P and Chen J 2007 Physica A 385 707
|
[21] |
Dorogovtsev S N, Goltsev A V and Mendes J F F 2002 Phys. Rev. E 65 066122
|
[22] |
Thomason A 1987 North-Holland Mathematics Studies 144 307
|
[23] |
Chung F R K, Graham R L and Wilson R M 1989 Combinatorica 9 345
|
[24] |
Barabasi A L and Albert R 1999 Science 286 509
|
[25] |
Zou Z Y, Liu P, Li L and Gao J Z 2012 Chin. Phys. B 21 028904
|
[26] |
Watts D J and Strogatz S H 1998 Nature 393 440
|
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