English
Related papers

Related papers: Damage Spreading in Spatial and Small-world Random…

200 papers

We give exact relations which are valid for small-world networks (SWN's) with a general `degree distribution', i.e the distribution of nearest-neighbor connections. For the original SWN model, we illustrate how these exact relations can be…

Disordered Systems and Neural Networks · Physics 2009-11-07 E. Almaas , R. V. Kulkarni , D. Stroud

Fixed points are fundamental states in any dynamical system. In the case of gene regulatory networks (GRNs) they correspond to stable genes profiles associated to the various cell types. We use Kauffman's approach to model GRNs with random…

Cell Behavior · Quantitative Biology 2012-03-08 Pablo Moisset de Espanés , Axel Osses , Iván Rapaport

Spreading dynamics of information and diseases are usually analyzed by using a unified framework and analogous models. In this paper, we propose a model to emphasize the essential difference between information spreading and epidemic…

Physics and Society · Physics 2015-05-28 Linyuan Lü , Duan-Bing Chen , Tao Zhou

We describe how noise propagates through a network by calculating the variance of the outputs. Using stochastic calculus and dynamical systems theory, we study the network topologies that accentuate or alleviate the effect of random…

Molecular Networks · Quantitative Biology 2011-08-15 Dionysios Barmpoutis , Richard M. Murray

Recurrent neural networks (RNNs) are widely used throughout neuroscience as models of local neural activity. Many properties of single RNNs are well characterized theoretically, but experimental neuroscience has moved in the direction of…

Machine Learning · Computer Science 2023-01-31 Leo Kozachkov , Michaela Ennis , Jean-Jacques Slotine

In a sensor network, in practice, the communication among sensors is subject to:(1) errors or failures at random times; (3) costs; and(2) constraints since sensors and networks operate under scarce resources, such as power, data rate, or…

Information Theory · Computer Science 2009-11-13 Soummya Kar , Jose M. F. Moura

Recurrent Neural Networks (RNNs) frequently exhibit complicated dynamics, and their sensitivity to the initialization process often renders them notoriously hard to train. Recent works have shed light on such phenomena analyzing when…

Machine Learning · Computer Science 2022-10-12 Vaggos Chatziafratis , Ioannis Panageas , Clayton Sanford , Stelios Andrew Stavroulakis

Susceptibility of scale free Power Law (PL) networks to attacks has been traditionally studied in the context of what may be termed as {\em instantaneous attacks}, where a randomly selected set of nodes and edges are deleted while the…

Statistical Mechanics · Physics 2007-05-23 Behnam A. Rezaei , Nima Sarshar , P. Oscar Boykin , Vwani P. Roychowdhury

Recent results from statistical physics show that large classes of complex networks, both man-made and of natural origin, are characterized by high clustering properties yet strikingly short path lengths between pairs of nodes. This class…

Information Theory · Computer Science 2016-11-17 Rui A. Costa , Joao Barros

In wireless networks, the knowledge of nodal distances is essential for several areas such as system configuration, performance analysis and protocol design. In order to evaluate distance distributions in random networks, the underlying…

Information Theory · Computer Science 2012-01-24 Sunil Srinivasa , Martin Haenggi

Growing networks have a causal structure. We show that the causality strongly influences the scaling and geometrical properties of the network. In particular the average distance between nodes is smaller for causal networks than for…

Disordered Systems and Neural Networks · Physics 2009-11-11 P. Bialas , Z. Burda , B. Waclaw

Random scale-free networks are ultrasmall worlds. The average length of the shortest paths in networks of size N scales as lnlnN. Here we show that these ultrasmall worlds can be navigated in ultrashort time. Greedy routing on scale-free…

Disordered Systems and Neural Networks · Physics 2009-02-08 Marian Boguna , Dmitri Krioukov

We introduce the concept of self-healing in the field of complex networks. Obvious applications range from infrastructural to technological networks. By exploiting the presence of redundant links in recovering the connectivity of the…

Physics and Society · Physics 2014-03-05 Walter Quattrociocchi , Guido Caldarelli , Antonio Scala

A complete understanding of real networks requires us to understand the consequences of the uneven interaction strengths between a system's components. Here we use the minimum spanning tree (MST) to explore the effect of weight assignment…

Disordered Systems and Neural Networks · Physics 2007-05-23 P. J. Macdonald , E. Almaas , A. -L. Barabasi

Communication networks are vulnerable to natural disasters, such as earthquakes or floods, as well as to physical attacks, such as an Electromagnetic Pulse (EMP) attack. Such real-world events happen at specific geographical locations and…

Systems and Control · Computer Science 2013-12-25 Omer Gold , Reuven Cohen

Recent studies of attacks on complex networks suggest that small initial breakdowns can lead to global cascades of overload failures in communication, economic trading, and supply-transportation systems, considering the defense methods is…

Disordered Systems and Neural Networks · Physics 2007-05-23 Yukio Hayashi , Toshiyuki Miyazaki

A small-world topology characterizes many complex systems including the structural and functional organization of brain networks. The topology allows simultaneously for local and global efficiency in the interaction of the system…

Physics and Society · Physics 2015-05-30 Sinisa Pajevic , Dietmar Plenz

We study the vulnerability of dominating sets against random and targeted node removals in complex networks. While small, cost-efficient dominating sets play a significant role in controllability and observability of these networks, a fixed…

Physics and Society · Physics 2015-06-12 F. Molnar , N. Derzsy , B. K. Szymanski , G. Korniss

Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, neural…

Statistical Mechanics · Physics 2015-05-20 Marc Barthelemy

Percolation theory characterizing the robustness of a network has applications ranging from biology, to epidemic spreading, and complex infrastructures. Percolation theory, however, only concern the typical response of a infinite network to…

Disordered Systems and Neural Networks · Physics 2018-02-28 Ginestra Bianconi
‹ Prev 1 3 4 5 6 7 10 Next ›