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Signal Processing Theory and Methods

Neighborhood-Preserving Translations on Graphs

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Authors:
Nicolas Grelier, Bastien Pasdeloup, Jean-Charles Vialatte, Vincent Gripon
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6 December 2016 - 7:58pm
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[1] Nicolas Grelier, Bastien Pasdeloup, Jean-Charles Vialatte, Vincent Gripon, "Neighborhood-Preserving Translations on Graphs", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1380. Accessed: Jun. 24, 2017.
@article{1380-16,
url = {http://sigport.org/1380},
author = {Nicolas Grelier; Bastien Pasdeloup; Jean-Charles Vialatte; Vincent Gripon },
publisher = {IEEE SigPort},
title = {Neighborhood-Preserving Translations on Graphs},
year = {2016} }
TY - EJOUR
T1 - Neighborhood-Preserving Translations on Graphs
AU - Nicolas Grelier; Bastien Pasdeloup; Jean-Charles Vialatte; Vincent Gripon
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1380
ER -
Nicolas Grelier, Bastien Pasdeloup, Jean-Charles Vialatte, Vincent Gripon. (2016). Neighborhood-Preserving Translations on Graphs. IEEE SigPort. http://sigport.org/1380
Nicolas Grelier, Bastien Pasdeloup, Jean-Charles Vialatte, Vincent Gripon, 2016. Neighborhood-Preserving Translations on Graphs. Available at: http://sigport.org/1380.
Nicolas Grelier, Bastien Pasdeloup, Jean-Charles Vialatte, Vincent Gripon. (2016). "Neighborhood-Preserving Translations on Graphs." Web.
1. Nicolas Grelier, Bastien Pasdeloup, Jean-Charles Vialatte, Vincent Gripon. Neighborhood-Preserving Translations on Graphs [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1380

MORPHOLOGICAL PDES ON GRAPHS FOR ANALYZING UNORGANIZED DATA IN 3D AND HIGHER

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Authors:
Abderrahim Elmoataz, François Lozes, Hugues Talbot
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6 December 2016 - 2:04pm
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[1] Abderrahim Elmoataz, François Lozes, Hugues Talbot, "MORPHOLOGICAL PDES ON GRAPHS FOR ANALYZING UNORGANIZED DATA IN 3D AND HIGHER", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1373. Accessed: Jun. 24, 2017.
@article{1373-16,
url = {http://sigport.org/1373},
author = {Abderrahim Elmoataz; François Lozes; Hugues Talbot },
publisher = {IEEE SigPort},
title = {MORPHOLOGICAL PDES ON GRAPHS FOR ANALYZING UNORGANIZED DATA IN 3D AND HIGHER},
year = {2016} }
TY - EJOUR
T1 - MORPHOLOGICAL PDES ON GRAPHS FOR ANALYZING UNORGANIZED DATA IN 3D AND HIGHER
AU - Abderrahim Elmoataz; François Lozes; Hugues Talbot
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1373
ER -
Abderrahim Elmoataz, François Lozes, Hugues Talbot. (2016). MORPHOLOGICAL PDES ON GRAPHS FOR ANALYZING UNORGANIZED DATA IN 3D AND HIGHER. IEEE SigPort. http://sigport.org/1373
Abderrahim Elmoataz, François Lozes, Hugues Talbot, 2016. MORPHOLOGICAL PDES ON GRAPHS FOR ANALYZING UNORGANIZED DATA IN 3D AND HIGHER. Available at: http://sigport.org/1373.
Abderrahim Elmoataz, François Lozes, Hugues Talbot. (2016). "MORPHOLOGICAL PDES ON GRAPHS FOR ANALYZING UNORGANIZED DATA IN 3D AND HIGHER." Web.
1. Abderrahim Elmoataz, François Lozes, Hugues Talbot. MORPHOLOGICAL PDES ON GRAPHS FOR ANALYZING UNORGANIZED DATA IN 3D AND HIGHER [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1373

Graph Frequency Analysis of Brain Signals


This paper presents methods to analyze functional brain networks and signals from graph spectral perspectives. The notion of frequency and filters traditionally defined for signals supported on regular domains such as discrete time and image grids has been recently generalized to irregular graph domains, and defines brain graph frequencies associated with different levels of spatial smoothness across the brain regions. Brain network frequency also enables the decomposition of brain signals into pieces corresponding to smooth or rapid variations.

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Authors:
Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, and Alejandro Ribeiro
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19 July 2016 - 1:47pm
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projectSummary_2016_IEEE.pdf

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[1] Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, and Alejandro Ribeiro, "Graph Frequency Analysis of Brain Signals", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1134. Accessed: Jun. 24, 2017.
@article{1134-16,
url = {http://sigport.org/1134},
author = {Weiyu Huang; Leah Goldsberry; Nicholas F. Wymbs; Scott T. Grafton; Danielle S. Bassett; and Alejandro Ribeiro },
publisher = {IEEE SigPort},
title = {Graph Frequency Analysis of Brain Signals},
year = {2016} }
TY - EJOUR
T1 - Graph Frequency Analysis of Brain Signals
AU - Weiyu Huang; Leah Goldsberry; Nicholas F. Wymbs; Scott T. Grafton; Danielle S. Bassett; and Alejandro Ribeiro
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1134
ER -
Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, and Alejandro Ribeiro. (2016). Graph Frequency Analysis of Brain Signals. IEEE SigPort. http://sigport.org/1134
Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, and Alejandro Ribeiro, 2016. Graph Frequency Analysis of Brain Signals. Available at: http://sigport.org/1134.
Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, and Alejandro Ribeiro. (2016). "Graph Frequency Analysis of Brain Signals." Web.
1. Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, and Alejandro Ribeiro. Graph Frequency Analysis of Brain Signals [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1134

IEEE SP Cup 2016 Project Report by Team "10Hertz": Exploring Power Signals for Location Forensics of Media Recordings


Electric Network Frequency is the frequency of power distribution networks in power grids that fluctuates about a nominal value with respect to the changing loads.Its ubiquitous nature has made notable contributions to forensic analysis that has substantiated its use as a significant tool in this area. In this paper we have proposed a technique to identify the power grid in which the ENF containing signal was recorded, without the assistance of concurrent power references.

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Authors:
Abhijith A., Abhinash V., Sreekiran A.R.,Tom Jose
Submitted On:
12 July 2016 - 10:53am
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[1] Abhijith A., Abhinash V., Sreekiran A.R.,Tom Jose, "IEEE SP Cup 2016 Project Report by Team "10Hertz": Exploring Power Signals for Location Forensics of Media Recordings", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1132. Accessed: Jun. 24, 2017.
@article{1132-16,
url = {http://sigport.org/1132},
author = {Abhijith A.; Abhinash V.; Sreekiran A.R.;Tom Jose },
publisher = {IEEE SigPort},
title = {IEEE SP Cup 2016 Project Report by Team "10Hertz": Exploring Power Signals for Location Forensics of Media Recordings},
year = {2016} }
TY - EJOUR
T1 - IEEE SP Cup 2016 Project Report by Team "10Hertz": Exploring Power Signals for Location Forensics of Media Recordings
AU - Abhijith A.; Abhinash V.; Sreekiran A.R.;Tom Jose
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1132
ER -
Abhijith A., Abhinash V., Sreekiran A.R.,Tom Jose. (2016). IEEE SP Cup 2016 Project Report by Team "10Hertz": Exploring Power Signals for Location Forensics of Media Recordings. IEEE SigPort. http://sigport.org/1132
Abhijith A., Abhinash V., Sreekiran A.R.,Tom Jose, 2016. IEEE SP Cup 2016 Project Report by Team "10Hertz": Exploring Power Signals for Location Forensics of Media Recordings. Available at: http://sigport.org/1132.
Abhijith A., Abhinash V., Sreekiran A.R.,Tom Jose. (2016). "IEEE SP Cup 2016 Project Report by Team "10Hertz": Exploring Power Signals for Location Forensics of Media Recordings." Web.
1. Abhijith A., Abhinash V., Sreekiran A.R.,Tom Jose. IEEE SP Cup 2016 Project Report by Team "10Hertz": Exploring Power Signals for Location Forensics of Media Recordings [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1132

A HIGH PERFORMANCE BASEBAND INSTRUMENT


Testing complex digital signal processors (DSPs) requires a development platform with sufficient
signal bandwidth and system performance to fully exercise the DSP. Without a development plat-
form, verification of DSPs would be limited to monitoring test output signals for an indication of
performance and successful operation. In addition, a development platform with high-speed analog
input and output interfaces to the DSP system allows it to be used directly in many sophisticated

Paper Details

Authors:
Jeremy Webb, Bevan Baas
Submitted On:
30 June 2016 - 2:14am
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jwwebb.sigport.6.29.2016.pdf

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[1] Jeremy Webb, Bevan Baas, "A HIGH PERFORMANCE BASEBAND INSTRUMENT", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1130. Accessed: Jun. 24, 2017.
@article{1130-16,
url = {http://sigport.org/1130},
author = {Jeremy Webb; Bevan Baas },
publisher = {IEEE SigPort},
title = {A HIGH PERFORMANCE BASEBAND INSTRUMENT},
year = {2016} }
TY - EJOUR
T1 - A HIGH PERFORMANCE BASEBAND INSTRUMENT
AU - Jeremy Webb; Bevan Baas
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1130
ER -
Jeremy Webb, Bevan Baas. (2016). A HIGH PERFORMANCE BASEBAND INSTRUMENT. IEEE SigPort. http://sigport.org/1130
Jeremy Webb, Bevan Baas, 2016. A HIGH PERFORMANCE BASEBAND INSTRUMENT. Available at: http://sigport.org/1130.
Jeremy Webb, Bevan Baas. (2016). "A HIGH PERFORMANCE BASEBAND INSTRUMENT." Web.
1. Jeremy Webb, Bevan Baas. A HIGH PERFORMANCE BASEBAND INSTRUMENT [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1130

Robust Beamforming based on Minimum Dispersion Criterion


In this presentation, the topic of robust beamforming is studied. We devise the minimum dispersion criterion which extends the minimum variance criterion from l2‐norm to lp‐norm. Formulations with different linear and nonlinear constraints are examined. The proposed framework generalizes existing approaches including the Capon and linearly constrained minimum variance beamformers as well as the method based on worst-case performance optimization. Computationally attractive algorithm realizations are also developed.

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Submitted On:
26 June 2016 - 10:03am
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[1] , "Robust Beamforming based on Minimum Dispersion Criterion", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1128. Accessed: Jun. 24, 2017.
@article{1128-16,
url = {http://sigport.org/1128},
author = { },
publisher = {IEEE SigPort},
title = {Robust Beamforming based on Minimum Dispersion Criterion},
year = {2016} }
TY - EJOUR
T1 - Robust Beamforming based on Minimum Dispersion Criterion
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1128
ER -
. (2016). Robust Beamforming based on Minimum Dispersion Criterion. IEEE SigPort. http://sigport.org/1128
, 2016. Robust Beamforming based on Minimum Dispersion Criterion. Available at: http://sigport.org/1128.
. (2016). "Robust Beamforming based on Minimum Dispersion Criterion." Web.
1. . Robust Beamforming based on Minimum Dispersion Criterion [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1128

Tutorial Slides for Convex Optimization Techniques for Super-Resolution Parameter Estimation

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Authors:
Yuejie Chi, Gongguo Tang
Submitted On:
30 March 2016 - 3:28am
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ICASSP2016tutorial_revised.pdf

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[1] Yuejie Chi, Gongguo Tang, "Tutorial Slides for Convex Optimization Techniques for Super-Resolution Parameter Estimation", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1069. Accessed: Jun. 24, 2017.
@article{1069-16,
url = {http://sigport.org/1069},
author = {Yuejie Chi; Gongguo Tang },
publisher = {IEEE SigPort},
title = {Tutorial Slides for Convex Optimization Techniques for Super-Resolution Parameter Estimation},
year = {2016} }
TY - EJOUR
T1 - Tutorial Slides for Convex Optimization Techniques for Super-Resolution Parameter Estimation
AU - Yuejie Chi; Gongguo Tang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1069
ER -
Yuejie Chi, Gongguo Tang. (2016). Tutorial Slides for Convex Optimization Techniques for Super-Resolution Parameter Estimation. IEEE SigPort. http://sigport.org/1069
Yuejie Chi, Gongguo Tang, 2016. Tutorial Slides for Convex Optimization Techniques for Super-Resolution Parameter Estimation. Available at: http://sigport.org/1069.
Yuejie Chi, Gongguo Tang. (2016). "Tutorial Slides for Convex Optimization Techniques for Super-Resolution Parameter Estimation." Web.
1. Yuejie Chi, Gongguo Tang. Tutorial Slides for Convex Optimization Techniques for Super-Resolution Parameter Estimation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1069

Are there approximate Fast Fourier Transforms on graphs ?

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Authors:
Luc Le Magoarou, Rémi Gribonval
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29 March 2016 - 3:34am
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[1] Luc Le Magoarou, Rémi Gribonval, "Are there approximate Fast Fourier Transforms on graphs ?", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1063. Accessed: Jun. 24, 2017.
@article{1063-16,
url = {http://sigport.org/1063},
author = {Luc Le Magoarou; Rémi Gribonval },
publisher = {IEEE SigPort},
title = {Are there approximate Fast Fourier Transforms on graphs ?},
year = {2016} }
TY - EJOUR
T1 - Are there approximate Fast Fourier Transforms on graphs ?
AU - Luc Le Magoarou; Rémi Gribonval
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1063
ER -
Luc Le Magoarou, Rémi Gribonval. (2016). Are there approximate Fast Fourier Transforms on graphs ?. IEEE SigPort. http://sigport.org/1063
Luc Le Magoarou, Rémi Gribonval, 2016. Are there approximate Fast Fourier Transforms on graphs ?. Available at: http://sigport.org/1063.
Luc Le Magoarou, Rémi Gribonval. (2016). "Are there approximate Fast Fourier Transforms on graphs ?." Web.
1. Luc Le Magoarou, Rémi Gribonval. Are there approximate Fast Fourier Transforms on graphs ? [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1063

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

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Authors:
Nicolas TREMBLAY, Gilles PUY, Pierre BORGNAT, Rémi GRIBONVAL, Pierre VANDERGHEYNST
Submitted On:
24 March 2016 - 12:06am
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talk_ICASSP_2016.pdf

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[1] Nicolas TREMBLAY, Gilles PUY, Pierre BORGNAT, Rémi GRIBONVAL, Pierre VANDERGHEYNST, "Accelerated Spectral Clustering Using Graph Filtering of Random Signals", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1017. Accessed: Jun. 24, 2017.
@article{1017-16,
url = {http://sigport.org/1017},
author = {Nicolas TREMBLAY; Gilles PUY; Pierre BORGNAT; Rémi GRIBONVAL; Pierre VANDERGHEYNST },
publisher = {IEEE SigPort},
title = {Accelerated Spectral Clustering Using Graph Filtering of Random Signals},
year = {2016} }
TY - EJOUR
T1 - Accelerated Spectral Clustering Using Graph Filtering of Random Signals
AU - Nicolas TREMBLAY; Gilles PUY; Pierre BORGNAT; Rémi GRIBONVAL; Pierre VANDERGHEYNST
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1017
ER -
Nicolas TREMBLAY, Gilles PUY, Pierre BORGNAT, Rémi GRIBONVAL, Pierre VANDERGHEYNST. (2016). Accelerated Spectral Clustering Using Graph Filtering of Random Signals. IEEE SigPort. http://sigport.org/1017
Nicolas TREMBLAY, Gilles PUY, Pierre BORGNAT, Rémi GRIBONVAL, Pierre VANDERGHEYNST, 2016. Accelerated Spectral Clustering Using Graph Filtering of Random Signals. Available at: http://sigport.org/1017.
Nicolas TREMBLAY, Gilles PUY, Pierre BORGNAT, Rémi GRIBONVAL, Pierre VANDERGHEYNST. (2016). "Accelerated Spectral Clustering Using Graph Filtering of Random Signals." Web.
1. Nicolas TREMBLAY, Gilles PUY, Pierre BORGNAT, Rémi GRIBONVAL, Pierre VANDERGHEYNST. Accelerated Spectral Clustering Using Graph Filtering of Random Signals [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1017

ProSparse Denoise: Prony's based Sparse Pattern Recovery in the Presence of Noise

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Authors:
Jon Onativia, Yue M. Lu, Pier Luigi Dragotti
Submitted On:
21 March 2016 - 10:31am
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IcasspProSparse16.pdf

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[1] Jon Onativia, Yue M. Lu, Pier Luigi Dragotti, "ProSparse Denoise: Prony's based Sparse Pattern Recovery in the Presence of Noise", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/927. Accessed: Jun. 24, 2017.
@article{927-16,
url = {http://sigport.org/927},
author = {Jon Onativia; Yue M. Lu; Pier Luigi Dragotti },
publisher = {IEEE SigPort},
title = {ProSparse Denoise: Prony's based Sparse Pattern Recovery in the Presence of Noise},
year = {2016} }
TY - EJOUR
T1 - ProSparse Denoise: Prony's based Sparse Pattern Recovery in the Presence of Noise
AU - Jon Onativia; Yue M. Lu; Pier Luigi Dragotti
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/927
ER -
Jon Onativia, Yue M. Lu, Pier Luigi Dragotti. (2016). ProSparse Denoise: Prony's based Sparse Pattern Recovery in the Presence of Noise. IEEE SigPort. http://sigport.org/927
Jon Onativia, Yue M. Lu, Pier Luigi Dragotti, 2016. ProSparse Denoise: Prony's based Sparse Pattern Recovery in the Presence of Noise. Available at: http://sigport.org/927.
Jon Onativia, Yue M. Lu, Pier Luigi Dragotti. (2016). "ProSparse Denoise: Prony's based Sparse Pattern Recovery in the Presence of Noise." Web.
1. Jon Onativia, Yue M. Lu, Pier Luigi Dragotti. ProSparse Denoise: Prony's based Sparse Pattern Recovery in the Presence of Noise [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/927

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