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
Link To Document