• DocumentCode
    257900
  • Title

    Combinatorial invariants of multidimensional topological network data

  • Author

    Henselman, Gregory ; Dlotko, Pawel

  • Author_Institution
    Electr. & Syst. Eng. Dept., Univ. of Pennsylvania Philadelphia, Philadelphia, PA, USA
  • fYear
    2014
  • fDate
    3-5 Dec. 2014
  • Firstpage
    828
  • Lastpage
    832
  • Abstract
    Modern applications of algebraic topology to point-cloud data analysis have motivated active investigation of combinatorial clique complexes - multidimensional extensions of combinatorial graphs. We show that meaningful invariants of such spaces are reflected in the combinatorial properties of an associated family of linear matroids and discuss matroid-theoretic approaches to several problems in computational topology. Our results allow us to derive estimates of the summary statistics of related constructs for random point cloud data, which we discuss for several sampling distributions in R2 and R3.
  • Keywords
    graph theory; matrix algebra; algebraic topology; combinatorial clique complexes; combinatorial graphs; combinatorial invariants; combinatorial properties; computational topology; linear matroids; matroid-theoretic approaches; multidimensional extensions; multidimensional topological network data; point-cloud data analysis; sampling distributions; Graphics; Network theory (graphs); Network topology; Sensors; Standards; Topology; embedding problem; matroid connectivity; matroid minor; max-flow min-cut; random topology; topological data analysis; wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference on
  • Conference_Location
    Atlanta, GA
  • Type

    conf

  • DOI
    10.1109/GlobalSIP.2014.7032235
  • Filename
    7032235