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 :
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