DocumentCode
3161068
Title
Approximating signals supported on graphs
Author
Zhu, Xiaofan ; Rabbat, Michael
Author_Institution
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
fYear
2012
fDate
25-30 March 2012
Firstpage
3921
Lastpage
3924
Abstract
In this paper, we introduce the concept of smoothness for signals supported on the vertices of a graph. We provide theoretical explanations when and why the Laplacian eigenbasis can be regarded as a meaningful “Fourier” transform of such signals. Moreover, we analyze the desired properties of the underlying graphs for better compressibility of the signals. We verify our theoretical work by experiments on real world data.
Keywords
Fourier transforms; Laplace transforms; approximation theory; eigenvalues and eigenfunctions; signal processing; Fourier transform; Laplacian eigenbasis; graph vertices; signal approximation; signal compressibility; Compressed sensing; Eigenvalues and eigenfunctions; Fourier transforms; Laplace equations; Linear approximation; Sensors; Fourier transform; Graph Laplacian; compressibility; smoothness;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location
Kyoto
ISSN
1520-6149
Print_ISBN
978-1-4673-0045-2
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2012.6288775
Filename
6288775
Link To Document