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Coupled neural networks, the Internet, World Wide Web, social networks and interacting biological networks are few examples of systems which consist of a large number of interacting dynamical units. Collective behavior of such systems is a consequence of t ...
The framework of complex networks has been shown to describe adequately a wide class of complex systems made up of a large number of interacting units. In this framework, a node is associated to each unit and two nodes are connected by an edge if the two u ...
Using the approximate conformal invariance of QCD at high energies we consider a simple AdS black disk model to describe saturation in DIS. Deep inside saturation the structure functions have the same power law scaling, F(T) similar to F(L) similar to x(-o ...
In this paper we investigate optimization of synchronization cost in undirected dynamical networks. To do so, proper weights are assigned to the networks’ edges considering node and edge betweenness centrality measures. The proposed method gives near-optim ...
Since the seminal work of Watts in the late 90s [1], graph-theoretic analyses have been performed on many complex dynamic networks, including brain structures [2]. Most studies have focused on functional connectivity defined between whole brain regions, us ...
Mobile wireless networks frequently possess, at the same time, both dense and sparse regions of connectivity; for example, due to a heterogeneous node distribution or radio propagation environment. This paper is about modeling both the mobility and the for ...
We want to extend the approximation of the error probability via a scaling approach from the BEC to general binary-input memoryless output-symmetric (BMS) channels. In particular, we consider such scaling laws for regular LDPC ensembles and message-passing ...
In this paper, we list four different interpretations of synchronizability, study their profile in different network structures and give evidence that they do not coincide, in general. By changing the network topological properties, their behavior is track ...
According to different kinds of connectivity, we can distinguish three types of mobile ad-hoc networks: dense, sparse and clustered networks. This paper is about modeling mobility in clustered networks, where nodes are concentrated into clusters of dense c ...
Dynamical networks with diffusive couplings are investigated from the point of view of synchronizability. Arbitrary connection graphs are admitted but the coupling is symmetric. Networks with equal interaction coefficients for all edges of the interaction ...
