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Gabriel Graph
In mathematics and computational geometry, the Gabriel graph of a set S of points in the Euclidean plane expresses one notion of proximity or nearness of those points. Formally, it is the graph G with vertex set S in which any two distinct points p \in S and q \in S are adjacent precisely when the closed disc having pq as a diameter contains no other points. Another way of expressing the same adjacency criterion is that p and q should be the two closest given points to their midpoint, with no other given point being as close. Gabriel graphs naturally generalize to higher dimensions, with the empty disks replaced by empty closed balls. Gabriel graphs are named after K. Ruben Gabriel, who introduced them in a paper with Robert R. Sokal in 1969. Percolation For Gabriel graphs of infinite random point sets, the finite site percolation threshold gives the fraction of points needed to support connectivity: if a random subset of fewer vertices than the threshold is given, the re ...
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Delaunay Triangulation
In mathematics and computational geometry, a Delaunay triangulation (also known as a Delone triangulation) for a given set P of discrete points in a general position is a triangulation DT(P) such that no point in P is inside the circumcircle of any triangle in DT(P). Delaunay triangulations maximize the minimum of all the angles of the triangles in the triangulation; they tend to avoid sliver triangles. The triangulation is named after Boris Delaunay for his work on this topic from 1934. For a set of points on the same line there is no Delaunay triangulation (the notion of triangulation is degenerate for this case). For four or more points on the same circle (e.g., the vertices of a rectangle) the Delaunay triangulation is not unique: each of the two possible triangulations that split the quadrangle into two triangles satisfies the "Delaunay condition", i.e., the requirement that the circumcircles of all triangles have empty interiors. By considering circumscribed spheres ...
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European Physical Journal B
''The European Physical Journal B: Condensed Matter and Complex Systems'' is a peer-reviewed scientific journal that covers condensed matter physics, statistical and nonlinear physics, and complex systems. Part of the ''European Physical Journal'' series, it is jointly published by EDP Sciences, the Società Italiana di Fisica, and Springer Science+Business Media. Abstracting and indexing ''The European Physical Journal B'' is indexed in the following databases: *Science Citation Index *Journal Citation Reports *Materials Science Citation Index *Chemical Abstracts Service * CSA - ProQuest *Zentralblatt Math See also *''European Physical Journal The ''European Physical Journal'' (or ''EPJ'') is a joint publication of EDP Sciences, Springer Science+Business Media, and the Società Italiana di Fisica. It arose in 1998 as a merger and continuation of ''Acta Physica Hungarica'', '' Anales d ...'' References Physics journals Springer Science+Business Media academic journal ...
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Systematic Biology
Biological systematics is the study of the diversification of living forms, both past and present, and the relationships among living things through time. Relationships are visualized as evolutionary trees (synonyms: cladograms, phylogenetic trees, phylogenies). Phylogenies have two components: branching order (showing group relationships) and branch length (showing amount of evolution). Phylogenetic trees of species and higher taxa are used to study the evolution of traits (e.g., anatomical or molecular characteristics) and the distribution of organisms ( biogeography). Systematics, in other words, is used to understand the evolutionary history of life on Earth. The word systematics is derived from the Latin word ''systema,'' which means systematic arrangement of organisms. Carl Linnaeus used 'Systema Naturae' as the title of his book. Branches and applications In the study of biological systematics, researchers use the different branches to further understand the relations ...
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SIAM Journal On Discrete Mathematics
'' SIAM Journal on Discrete Mathematics'' is a peer-reviewed mathematics journal published quarterly by the Society for Industrial and Applied Mathematics (SIAM). The journal includes articles on pure and applied discrete mathematics. It was established in 1988, along with the '' SIAM Journal on Matrix Analysis and Applications'', to replace the '' SIAM Journal on Algebraic and Discrete Methods''. The journal is indexed by ''Mathematical Reviews'' and Zentralblatt MATH. Its 2009 MCQ was 0.57. According to the ''Journal Citation Reports'', the journal has a 2016 impact factor of 0.755. Although its official ISO abbreviation is ''SIAM J. Discrete Math.'', its publisher and contributors frequently use the shorter abbreviation ''SIDMA''. References External links * Combinatorics journals Publications established in 1988 English-language journals Discrete Mathematics Discrete mathematics is the study of mathematical structures that can be considered "discrete" (in a wa ...
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Geometric Spanner
A geometric spanner or a -spanner graph or a -spanner was initially introduced as a weighted graph over a set of points as its vertices for which there is a -path between any pair of vertices for a fixed parameter . A -path is defined as a path through the graph with weight at most times the spatial distance between its endpoints. The parameter is called the stretch factor or dilation factor of the spanner. In computational geometry, the concept was first discussed by L.P. Chew in 1986, although the term "spanner" was not used in the original paper. The notion of graph spanners has been known in graph theory: -spanners are spanning subgraphs of graphs with similar dilation property, where distances between graph vertices are defined in graph-theoretical terms. Therefore geometric spanners are graph spanners of complete graphs embedded in the plane with edge weights equal to the distances between the embedded vertices in the corresponding metric. Spanners may be used in ...
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Beta-skeleton
In computational geometry and geometric graph theory, a ''β''-skeleton or beta skeleton is an undirected graph defined from a set of points in the Euclidean plane. Two points ''p'' and ''q'' are connected by an edge whenever all the angles ''prq'' are sharper than a threshold determined from the numerical parameter ''β''. Circle-based definition Let ''β'' be a positive real number, and calculate an angle ''θ'' using the formulas :\theta = \begin \sin^ \frac, & \text\beta \ge 1 \\ \pi - \sin^, & \text\beta\le 1\end For any two points ''p'' and ''q'' in the plane, let ''R''''pq'' be the set of points for which angle ''prq'' is greater than ''θ''. Then ''R''''pq'' takes the form of a union of two open disks with diameter ''βd''(''p'',''q'') for ''β'' ≥ 1 and ''θ'' ≤ π/2, and it takes the form of the intersection of two open disks with diameter ''d''(''p'',''q'')/''β'' for ''β'' ≤ 1 and ''θ'' ≥ π/2. When ''β''&n ...
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Nearest Neighbor Graph
The nearest neighbor graph (NNG) is a directed graph defined for a set of points in a metric space, such as the Euclidean distance in the plane. The NNG has a vertex for each point, and a directed edge from ''p'' to ''q'' whenever ''q'' is a nearest neighbor of ''p'', a point whose distance from ''p'' is minimum among all the given points other than ''p'' itself. In many uses of these graphs, the directions of the edges are ignored and the NNG is defined instead as an undirected graph. However, the nearest neighbor relation is not a symmetric one, i.e., ''p'' from the definition is not necessarily a nearest neighbor for ''q''. In theoretical discussions of algorithms a kind of general position is often assumed, namely, the nearest (k-nearest) neighbor is unique for each object. In implementations of the algorithms it is necessary to bear in mind that this is not always the case. For situations in which it is necessary to make the nearest neighbor for each object unique, the set ' ...
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Relative Neighborhood Graph
In computational geometry, the relative neighborhood graph (RNG) is an undirected graph defined on a set of points in the Euclidean plane by connecting two points p and q by an edge whenever there does not exist a third point r that is closer to both p and q than they are to each other. This graph was proposed by Godfried Toussaint in 1980 as a way of defining a structure from a set of points that would match human perceptions of the shape of the set.. Algorithms showed how to construct the relative neighborhood graph of n points in the plane efficiently in O(n\log n) time. It can be computed in O(n) expected time, for random set of points distributed uniformly in the unit square. The relative neighborhood graph can be computed in linear time from the Delaunay triangulation of the point set.. Generalizations Because it is defined only in terms of the distances between points, the relative neighborhood graph can be defined for point sets in any and for non-Euclidean metrics. Com ...
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Euclidean Minimum Spanning Tree
A Euclidean minimum spanning tree of a finite set of points in the Euclidean plane or higher-dimensional Euclidean space connects the points by a system of line segments with the points as endpoints, minimizing the total length of the segments. In it, any two points can reach each other along a path through the line segments. It can be found as the minimum spanning tree of a complete graph with the points as vertices and the Euclidean distances between points as edge weights. The edges of the minimum spanning tree meet at angles of at least 60°, at most six to a vertex. In higher dimensions, the number of edges per vertex is bounded by the kissing number of tangent unit spheres. The total length of the edges, for points in a unit square, is at most proportional to the square root of the number of points. Each edge lies in an empty region of the plane, and these regions can be used to prove that the Euclidean minimum spanning tree is a subgraph of other geometric graphs includin ...
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Linear Time
In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Thus, the amount of time taken and the number of elementary operations performed by the algorithm are taken to be related by a constant factor. Since an algorithm's running time may vary among different inputs of the same size, one commonly considers the worst-case time complexity, which is the maximum amount of time required for inputs of a given size. Less common, and usually specified explicitly, is the average-case complexity, which is the average of the time taken on inputs of a given size (this makes sense because there are only a finite number of possible inputs of a given size). In both cases, the time complexity is generally expresse ...
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