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Office: Room 2605,
Department of Mathematics,
Shanghai Jiao Tong University
Mail: xiaodong@sjtu.edu.cn
Mailing-Address: No.800,
Dong Chuan Road, Shanghai, P.C: 200240
Telephone: 54743148-2605
Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks. The study of networks, in the form of mathematical graph theory, is one of the fundamental pillars of discrete mathematics. First, it aims to ?nd and highlight statistical properties, such as path lengths and degree distributions, that characterize the structure and behavior of networked systems, and to suggest appropriate ways to measure these properties. Second, it aims to create models of networks that can help us to understand the meaning of these properties—how they came to be as they are, and how they interact with one another. Third, it aims to predict what the behavior of networked systems will be on the basis of measured structural properties and the local rules governing individual vertices.
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------最新论文------

Complete multipartite graphs are determined by their distancespectra...........
The inertia of weighted unicyclic graphs...........
A NEW ENTANGLEMENT MEASURE_D-CONCURRENCE...........
The signless Laplacian coefficients and incidence energy of bicyclic graphs.......3/3
Sharp bounds for the signless Laplacian spectral radius in terms of clique number.......3/1

上海交通大学数学系
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