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相关论文: Scaling properties of scale-free networks in degre…

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Recently, the concept of geometric renormalization group provides a good approach for studying the structural symmetry and functional invariance of complex networks. Along this line, we systematically investigate the finite-size scaling of…

物理与社会 · 物理学 2021-09-15 Dan Chen , Housheng Su , Xiaofan Wang , Gui-Jun Pan , Guanrong Chen

Scale-free networks are ubiquitous in social, biological and technological networked systems. Dynamic Scale-free networks and their synchronizations are important to understand and predict the behavior of social, biological and…

社会与信息网络 · 计算机科学 2024-09-16 Rakib Hassan Pran

Scaling behavior of scale-free evolving networks arising in communications, citations, collaborations, etc. areas is studied. We derive universal scaling relations describing properties of such networks and indicate limits of their…

凝聚态物理 · 物理学 2009-10-31 S. N. Dorogovtsev , J. F. F. Mendes

We analyze about two hundred naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned…

Scale free dynamics are observed in a variety of physical and biological systems. These include neural activity in which evidence for scale freeness has been reported using a range of imaging modalities. Here, we derive the ways in which…

Despite their diverse origin, networks of large real-world systems reveal a number of common properties including small-world phenomena, scale-free degree distributions and modularity. Recently, network self-similarity as a natural outcome…

适应与自组织系统 · 物理学 2012-02-09 Neli Blagus , Lovro Šubelj , Marko Bajec

Transport is an important function in many network systems and understanding its behavior on biological, social, and technological networks is crucial for a wide range of applications. However, it is a property that is not well-understood…

无序系统与神经网络 · 物理学 2009-11-13 Lazaros K. Gallos , Chaoming Song , Shlomo Havlin , Hernan A. Makse

Scaling factors in residual branches have emerged as a prevalent method for boosting neural network performance, especially in normalization-free architectures. While prior work has primarily examined scaling effects from an optimization…

机器学习 · 计算机科学 2026-05-26 Zixiong Yu , Guhan Chen , Jianfa Lai , Bohan Li , Songtao Tian

In this work we investigate the spectra of Laplacian matrices that determine many dynamic properties of scale-free networks below and at the percolation threshold. We use a replica formalism to develop analytically, based on an integral…

统计力学 · 物理学 2016-08-31 F. Jasch , C. von Ferber , A. Blumen

We extend the standard scale-free network model to include a ``triad formation step''. We analyze the geometric properties of networks generated by this algorithm both analytically and by numerical calculations, and find that our model…

无序系统与神经网络 · 物理学 2009-11-07 Petter Holme , Beom Jun Kim

In a recursive way and by including a parameter, we introduce a family of deterministic scale-free networks. The resulting networks exhibit small-world effects. We calculate the exact results for the degree exponent, the clustering…

统计力学 · 物理学 2007-05-23 Zhongzhi Zhang , Lili Rong

In general, the power-law degree distribution has profound influence on various dynamical processes defined on scale-free networks. In this paper, we will show that power-law degree distribution alone does not suffice to characterize the…

统计力学 · 物理学 2009-12-09 Zhongzhi Zhang , Weilen Xie , Shuigeng Zhou , Mo Li , Jihong Guan

We found that models of evolving random networks exhibit dynamic scaling similar to scaling of growing surfaces. It is demonstrated by numerical simulations of two variants of the model in which nodes are added as well as removed [Phys.…

统计力学 · 物理学 2009-11-07 Miroslav Kotrla , Frantisek Slanina , Jakub Steiner

Co-evolution exhibited by a network system, involving the intricate interplay between the dynamics of the network itself and the subsystems connected by it, is a key concept for understanding the self-organized, flexible nature of…

物理与社会 · 物理学 2012-11-14 Takaaki Aoki , Toshio Aoyagi

Recently, it has been claimed that some complex networks are self-similar under a convenient renormalization procedure. We present a general method to study renormalization flows in graphs. We find that the behavior of some variables under…

物理与社会 · 物理学 2009-11-13 Filippo Radicchi , José Javier Ramasco , Alain Barrat , Santo Fortunato

Many real-world scale-free networks, such as neural networks and online communication networks, consist of a fixed number of nodes but exhibit dynamic edge fluctuations. However, traditional models frequently overlook scenarios where the…

社会与信息网络 · 计算机科学 2026-04-02 Yichao Yao , Minyu Feng , Matjaž Perc , Jürgen Kurths

We have analysed some structural properties of scale-free networks with the same degree distribution. Departing from a degree distribution obtained from the Barab\'asi-Albert (BA) algorithm, networks were generated using four additional…

社会与信息网络 · 计算机科学 2013-06-04 José H. H. Grisi-Filho , Raul Ossada , Fernando Ferreira , Marcos Amaku

Synchronization problems in complex networks are very often studied by researchers due to its many applications to various fields such as neurobiology, e-commerce and completion of tasks. In particular, Scale Free networks with degree…

物理与社会 · 物理学 2015-07-07 Débora Torres , Matías A. Di Muro , Cristian E. La Rocca , Lidia A. Braunstein

Scale invariance profoundly influences the dynamics and structure of complex systems, spanning from critical phenomena to network architecture. Here, we propose a precise definition of scale-invariant networks by leveraging the concept of a…

统计力学 · 物理学 2024-12-17 Anna Poggialini , Pablo Villegas , Miguel A. Muñoz , Andrea Gabrielli

Many real-world complex networks simultaneously exhibit topological features of scale-free behaviour and hierarchical organization. In this regard, deterministic scale-free [A.-L. Barab\'asi \etal, Physica A, 299, 3 (2001)] and…

物理与社会 · 物理学 2017-11-22 Chiranjit Mitra , Jürgen Kurths , Reik V. Donner
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