Artificial neural networks, electronic circuits, and gene networks are some examples of systems that can be modeled as networks, that is, as collections of interconnected nodes. I...
Mattiussi, Claudio, Dürr, Peter, Marbach, Daniel ...
Abstract--In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discretetime stochastic complex networks with randomly occurr...
Abstract--Wireless networks, especially mobile ad hoc networks (MANET) and cognitive radio networks (CRN), are facing two new challenges beyond traditional random network model: op...
Complex networks capture interactions among entities in various application areas in a graph representation. Analyzing large scale complex networks often answers important question...
Networks have been used to describe and model a wide range of complex systems, both natural as well as man-made. One particularly interesting application in the earth sciences is t...
Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. ...
Concise and reliable graph-theoretic analysis of complex networks today is a cumbersome task, consisting essentially of the adaptation of intricate libraries for each specific pr...
Benjamin Schiller, Dirk Bradler, Immanuel Schweize...
Community detection is an important task for mining the structure and function of complex networks. Generally, there are several different kinds of nodes in a network which are c...
Jianbin Huang, Heli Sun, Jiawei Han, Hongbo Deng, ...
Brains are complex networks. Previously, we revealed that specific connected structures are either significantly abundant or rare in cortical networks. However, it remains unkno...
Background: Transcriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes...
Modular structure is ubiquitous in real-world complex networks. The detection of this type of organization into modules gives insights in the relationship between topological stru...