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Discrete Signal Processing on Graphs

Published on Apr 1, 2013in IEEE Transactions on Signal Processing5.23
· DOI :10.1109/TSP.2013.2238935
Aliaksei Sandryhaila18
Estimated H-index: 18
(CMU: Carnegie Mellon University),
Jose M. F. Moura56
Estimated H-index: 56
(CMU: Carnegie Mellon University)
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Abstract
In social settings, individuals interact through webs of relationships. Each individual is a node in a complex network (or graph) of interdependencies and generates data, lots of data. We label the data by its source, or formally stated, we index the data by the nodes of the graph. The resulting signals (data indexed by the nodes) are far removed from time or image signals indexed by well ordered time samples or pixels. DSP, discrete signal processing, provides a comprehensive, elegant, and efficient methodology to describe, represent, transform, analyze, process, or synthesize these well ordered time or image signals. This paper extends to signals on graphs DSP and its basic tenets, including filters, convolution, z-transform, impulse response, spectral representation, Fourier transform, frequency response, and illustrates DSP on graphs by classifying blogs, linear predicting and compressing data from irregularly located weather stations, or predicting behavior of customers of a mobile service provider.
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  • References (66)
  • Citations (612)
References66
Newest
#1Ameya Agaskar (Harvard University)H-Index: 7
#2Yue M. Lu (Harvard University)H-Index: 24
112 CitationsSource
May 1, 2013 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Aliaksei Sandryhaila (CMU: Carnegie Mellon University)H-Index: 18
#2Jose M. F. Moura (CMU: Carnegie Mellon University)H-Index: 56
24 CitationsSource
May 1, 2013 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Aliaksei Sandryhaila (CMU: Carnegie Mellon University)H-Index: 18
#2Jose M. F. Moura (CMU: Carnegie Mellon University)H-Index: 56
33 CitationsSource
#1Divyanshu Vats (UMN: University of Minnesota)H-Index: 7
#2Jose M. F. Moura (CMU: Carnegie Mellon University)H-Index: 56
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Sep 1, 2012 in ICIP (International Conference on Image Processing)
#1Aliaksei Sandryhaila (CMU: Carnegie Mellon University)H-Index: 18
#2Jose M. F. Moura (CMU: Carnegie Mellon University)H-Index: 56
11 CitationsSource
#1Sunil K. Narang (SC: University of Southern California)H-Index: 15
#2Antonio Ortega Diego (SC: University of Southern California)H-Index: 52
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#1Aliaksei Sandryhaila (CMU: Carnegie Mellon University)H-Index: 18
#2Jelena Kovacevic (CMU: Carnegie Mellon University)H-Index: 39
Last.Markus Püschel (ETH Zurich)H-Index: 36
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20 CitationsSource
Mar 1, 2012 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Ameya Agaskar (Harvard University)H-Index: 7
#2Yue M. Lu (Harvard University)H-Index: 24
21 CitationsSource
Mar 1, 2012 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Xiaofan Zhu (McGill University)H-Index: 2
#2Michael Rabbat (McGill University)H-Index: 31
103 CitationsSource
#1Aliaksei Sandryhaila (CMU: Carnegie Mellon University)H-Index: 18
#2Samir Saba (University of Pittsburgh)H-Index: 36
Last.Jelena Kovacevic (CMU: Carnegie Mellon University)H-Index: 39
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