Sökning: "Random graphs"

Visar resultat 1 - 5 av 44 avhandlingar innehållade orden Random graphs.

  1. 1. On Degree Variance in Random Graphs

    Författare :Jan Hagberg; Ove Frank; Tom A.B. Snijders; Stockholms universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Degree Sequences; Uniform Random Graphs; Bernoulli Graphs; Degree Moments; Degree Statistics; Degree Variance; Gamma Approximation; Centrality Testing; Integer Sequences; Statistics; Statistik;

    Sammanfattning : This thesis is concerned with degree moments and degree variance in random graphs. The degree of vertex i in a graph is the number of edges incident to vertex i.In the first paper, degree moments and functions of degree moments are investigated for three random graph models. LÄS MER

  2. 2. Random tournaments and random circuits

    Författare :Pontus Andersson; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; Mathematics; Poisson-Dirichlet distribution; random circuit decomposition; random tournament; subgraph count; MATEMATIK; MATHEMATICS; MATEMATIK; matematik; Mathematics;

    Sammanfattning : This thesis is devoted to two different topics in the area of probabilistic combinatorics: asymptotic behaviour of subgraph counts in a random tournament and random circuit decompositions of complete graphs.Let Tn be a random tournament on n vertices, chosen uniformly from all 2(n2) such tournaments, and let D be an arbitrary directed graph. LÄS MER

  3. 3. Dynamics in Random Boolean Networks

    Författare :Björn Samuelsson; Funktionell zoologi; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; gravitation; relativity; quantum mechanics; biomathematics biometrics; Bioinformatik; medicinsk informatik; biomatematik; Mathematical logic; set theory; combinatories; Matematisk logik; Mathematical and general theoretical physics; kombinatorik; mängdlära; classical mechanics; Bioinformatics; tissue simulations; transcription networks; random graphs; random maps; nested canalyzing; canalyzing; genetic regulation; Kauffman networks; random Boolean networks; statistical physics; thermodynamics; medical informatics; Matematisk och allmän teoretisk fysik; klassisk mekanik; kvantmekanik; relativitet; termodynamik; statistisk fysik;

    Sammanfattning : There are many examples of complex networks in science. It can be genetic regulation in living cells, computers on the Internet, or social and economic networks. In this context, Boolean networks provide simplistic models that are relatively easy to handle using computer simulations and mathematical methods. LÄS MER

  4. 4. Random railways and cycles in random regular graphs

    Författare :Hans Garmo; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; Mathematics; Random railway; connectivity number; random regular graph; long cycles; asymptotic distribution. 1991 Mathematics Subject Classification. Primary 60F05; 60C05; 05C38; 05C80; 05C40; 05C45; MATEMATIK; MATHEMATICS; MATEMATIK; matematisk statistik; Mathematical Statistics;

    Sammanfattning : In a cubic multigraph certain restrictions on the paths are made to define what is called a railway. Due to these restrictions a special kind of connectivity is defined. As the number of vertices tends to infinity, the asymptotic probability of obtaining an, in this sense, connected random cubic multigraph is shown to be 1/3. LÄS MER

  5. 5. Random geometric graphs and their applications in neuronal modelling

    Författare :Fioralba Ajazi; Matematisk statistik; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; random graph; Neural Network; Probability; Inhomogeneous random graph; random distance graph; random grown networks;

    Sammanfattning : Random graph theory is an important tool to study different problems arising from real world.In this thesis we study how to model connections between neurons (nodes) and synaptic connections (edges) in the brain using inhomogeneous random distance graph models. LÄS MER