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  2. Shuffle-exchange network - Wikipedia

    en.wikipedia.org/wiki/Shuffle-exchange_network

    The order-4 shuffle-exchange network, with its vertices arranged in numerical order. In graph theory, the shuffle-exchange network is an undirected cubic multigraph, whose vertices represent binary sequences of a given length and whose edges represent two operations on these sequence, circular shifts and flipping the lowest-order bit.

  3. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    Example of shuffling five letters using Durstenfeld's in-place version of the Fisher–Yates shuffle The Fisher–Yates shuffle is an algorithm for shuffling a finite sequence . The algorithm takes a list of all the elements of the sequence, and continually determines the next element in the shuffled sequence by randomly drawing an element from ...

  4. Line graph - Wikipedia

    en.wikipedia.org/wiki/Line_graph

    In the mathematical discipline of graph theory, the line graph of an undirected graph G is another graph L(G) that represents the adjacencies between edges of G. L(G) is constructed in the following way: for each edge in G, make a vertex in L(G); for every two edges in G that have a vertex in common, make an edge between their corresponding vertices in L(G).

  5. Random permutation - Wikipedia

    en.wikipedia.org/wiki/Random_permutation

    A simple algorithm to generate a permutation of n items uniformly at random without retries, known as the Fisher–Yates shuffle, is to start with any permutation (for example, the identity permutation), and then go through the positions 0 through n − 2 (we use a convention where the first element has index 0, and the last element has index n − 1), and for each position i swap the element ...

  6. Random graph - Wikipedia

    en.wikipedia.org/wiki/Random_graph

    Mashaghi A. et al., for example, demonstrated that a transformation which converts random graphs to their edge-dual graphs (or line graphs) produces an ensemble of graphs with nearly the same degree distribution, but with degree correlations and a significantly higher clustering coefficient. [9]

  7. Arrangement of lines - Wikipedia

    en.wikipedia.org/wiki/Arrangement_of_lines

    These graphs are partial cubes, graphs in which the nodes can be labeled by bitvectors in such a way that the graph distance equals the Hamming distance between labels. In the case of a line arrangement, each coordinate of the labeling assigns 0 to nodes on one side of one of the lines and 1 to nodes on the other side. [26]

  8. Edge dominating set - Wikipedia

    en.wikipedia.org/wiki/Edge_dominating_set

    Examples of edge dominating sets. In graph theory, an edge dominating set for a graph G = (V, E) is a subset D ⊆ E such that every edge not in D is adjacent to at least one edge in D. An edge dominating set is also known as a line dominating set. Figures (a)–(d) are examples of edge dominating sets (thick red lines).

  9. Reservoir sampling - Wikipedia

    en.wikipedia.org/wiki/Reservoir_sampling

    A natural approach would be to shuffle the deck and then take the top k cards. In the general case, the shuffle also needs to work even if the number of cards in the deck is not known in advance, a condition which is satisfied by the inside-out version of the Fisher–Yates shuffle : [ 9 ]