DocumentCode
257888
Title
Graph signal coarsening: Dimensionality reduction in irregular domain
Author
Pengfei Liu ; Xiaohan Wang ; Yuantao Gu
Author_Institution
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
fYear
2014
fDate
3-5 Dec. 2014
Firstpage
798
Lastpage
802
Abstract
Graph signal coarsening is a kind of dimensionality reduction in irregular domain. Given a graph signal, it aims to simultaneously obtain a coarser version of the graph and a coarsened signal on the new graph. In this work, we explore the design space for the graph signal coarsening problem and show that solutions can be split into four categories. We propose an effective method that uses a successive approach and spectral-domain-based signal coarsening for solving the problem, which is the first that falls into one of the four categories. Experiments are conducted to show the effectiveness of the proposed method.
Keywords
graph theory; signal processing; dimensionality reduction; graph signal coarsening problem; irregular domain; spectral-domain-based signal coarsening; Approximation algorithms; Communities; Eigenvalues and eigenfunctions; Laplace equations; Space exploration; Spectral analysis; dimensionality reduction; graph signal coarsening; graph signal processing; irregular domain; spectral graph theory;
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.2014.7032229
Filename
7032229
Link To Document