Results 11 to 20 of about 274,053 (268)
Physical Review E, 2002 We analyse graphs in which each vertex is assigned random coordinates in a geometric space of arbitrary dimensionality and only edges between adjacent points are present. The critical connectivity is found numerically by examining the size of the largest cluster. We derive an analytical expression for the cluster coefficient which shows that the graphs
Dall, J., Christensen, Michael
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On the Validity of Neural Mass Models
Frontiers in Computational Neuroscience, 2021 Modeling the dynamics of neural masses is a common approach in the study of neural populations. Various models have been proven useful to describe a plenitude of empirical observations including self-sustained local oscillations and patterns of distant ...
Nicolás Deschle +6 more
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The Electronic Journal of Combinatorics, 2009 We study a random even subgraph of a finite graph $G$ with a general edge-weight $p\in(0,1)$. We demonstrate how it may be obtained from a certain random-cluster measure on $G$, and we propose a sampling algorithm based on coupling from the past. A random even subgraph of a planar lattice undergoes a phase transition at the parameter-value ${1\over2 ...
Geoffrey R. Grimmett, Svante Janson
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Data Collection Based on Opportunistic Node Connections in Wireless Sensor Networks
Sensors, 2018 The working⁻sleeping cycle strategy used for sensor nodes with limited power supply in wireless sensor networks can effectively save their energy, but also causes opportunistic node connections due to the intermittent communication mode, which can ...
Guisong Yang, Zhiwei Peng, Xingyu He
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The Electronic Journal of Combinatorics, 2009 We introduce a pair of natural, equivalent models for random threshold graphs and use these models to deduce a variety of properties of random threshold graphs. Specifically, a random threshold graph $G$ is generated by choosing $n$ IID values $x_1,\ldots,x_n$ uniformly in $[0,1]$; distinct vertices $i,j$ of $G$ are adjacent exactly when $x_i + x_j \ge
Elizabeth Perez Reilly +1 more
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The Electronic Journal of Combinatorics, 2023 Let $N=\binom{n}{2}$ and $s\geq 2$. Let $e_{i,j},\,i=1,2,\ldots,N,\,j=1,2,\ldots,s$ be $s$ independent permutations of the edges $E(K_n)$ of the complete graph $K_n$. A MultiTree is a set $I\subseteq [N]$ such that the edge sets $E_{I,j}$ induce spanning trees for $j=1,2,\ldots,s$.
Alan M. Frieze, Wesley Pegden
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The rank of random graphs [PDF]
Random Structures & Algorithms, 2008 AbstractWe show that almost surely the rank of the adjacency matrix of the Erdős‐Rényi random graph G(n,p) equals the number of nonisolated vertices for any c ln n/n ≤ p ≤ 1/2, where c is an arbitrary positive constant larger than 1/2. In particular, the adjacency matrix of the giant component (a.s.) has full rank in this range.
Kevin P. Costello, Van H. Vu
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Physical Review Letters, 2002 We study the graph coloring problem over random graphs of finite average connectivity $c$. Given a number $q$ of available colors, we find that graphs with low connectivity admit almost always a proper coloring whereas graphs with high connectivity are uncolorable.
R. MULET +3 more
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On the Vertex-Connectivity of an Uncertain Random Graph
IEEE Access, 2020 In many practical problems, randomness and uncertainty simultaneously appear in one complex system or network. When graph theory is applied to these problems, these complex systems or networks are usually represented by uncertain random graphs, in which ...
Hao Li, Xin Gao
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Random Graph Isomorphism [PDF]
SIAM Journal on Computing, 1980 Summary: A straightforward linear time canonical labeling algorithm is shown to apply to almost all graphs (i.e. all but \(O(2^{\binom n2})\) of the \(2^{\binom n2})\) graphs on \(n\) vertices). Hence, for almost all graphs \(X\), and graph \(Y\) can be easily tested for isomorphism to \(X\) by an extremly naive linear time algorithm.
László Babai +2 more
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