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Multi-windowed graph Fourier frames
XIAN-WEI ZHENG1; YUAN YAN TANG1; JIAN-TAO ZHOU1; HAO-LIANG YUAN1; YU-LONG WANG1; LI-NA YANG2; JIAN-JIA PAN1
2017-03-06
Conference Name2016 International Conference on Machine Learning and Cybernetics (ICMLC)
Source PublicationProceedings of the 2016 International Conference on Machine Learning and Cybernetics
Volume2
Pages1042-1048
Conference Date10-13 July 2016
Conference PlaceJeju
CountrySouth Korea
PublisherIEEE
Abstract

Graph signal processing is a new research field in the signal processing community. Recently, windowed graph Fourier frames have been proposed to analyze graph signals. However, it is not easy to construct tight frames by using signal window function. In this paper, we extend the windowed graph Fourier transform to the multi-window case. The multi-windowed graph Fourier frames offer more freedom on constructing tight frames. We provide some results for constructing multi-windowed graph Fourier frames, dual frames and tight frames. When applying the multi-windowed graph Fourier transform on synthesis graph signals, a dual localization phenomenon can be found in the original and dual windowed graph Fourier transform coefficients.

KeywordDual Frames Graph Fourier Transform Tight Frames Windowed Graph Fourier Frames
DOIhttps://doi.org/10.1109/ICMLC.2016.7873023
URLView the original
Indexed By其他
Language英语
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Computer and Information Science, University of Macau 999078, Macau
2.School of Computer, Electronics and Information, Guangxi University, Nanning 530004, China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
XIAN-WEI ZHENG,YUAN YAN TANG,JIAN-TAO ZHOU,et al. Multi-windowed graph Fourier frames[C]:IEEE,2017:1042-1048.
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