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Sensor Array and Multichannel Signal Processing

COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION

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Authors:
Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li
Submitted On:
7 December 2016 - 2:56pm
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GlobalSIP16.pdf

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[1] Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li, "COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1412. Accessed: Feb. 25, 2017.
@article{1412-16,
url = {http://sigport.org/1412},
author = {Mohammadreza Ghorbaniparvar; Ning Zhou; Xiaohua Li },
publisher = {IEEE SigPort},
title = {COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION},
year = {2016} }
TY - EJOUR
T1 - COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION
AU - Mohammadreza Ghorbaniparvar; Ning Zhou; Xiaohua Li
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1412
ER -
Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li. (2016). COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION. IEEE SigPort. http://sigport.org/1412
Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li, 2016. COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION. Available at: http://sigport.org/1412.
Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li. (2016). "COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION." Web.
1. Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li. COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1412

COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION

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Authors:
Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li
Submitted On:
7 December 2016 - 2:39pm
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GlobalSIP16.pdf

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[1] Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li, "COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1411. Accessed: Feb. 25, 2017.
@article{1411-16,
url = {http://sigport.org/1411},
author = {Mohammadreza Ghorbaniparvar; Ning Zhou; Xiaohua Li },
publisher = {IEEE SigPort},
title = {COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION},
year = {2016} }
TY - EJOUR
T1 - COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION
AU - Mohammadreza Ghorbaniparvar; Ning Zhou; Xiaohua Li
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1411
ER -
Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li. (2016). COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION. IEEE SigPort. http://sigport.org/1411
Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li, 2016. COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION. Available at: http://sigport.org/1411.
Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li. (2016). "COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION." Web.
1. Mohammadreza Ghorbaniparvar, Ning Zhou, Xiaohua Li. COHERENCE FUNCTION ESTIMATION WITH A DERIVATIVE CONSTRAINT FOR POWER GRID OSCILLATION DETECTION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1411

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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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: Feb. 25, 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

Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics


Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics

In this paper, we present Discriminant Correlation Analysis (DCA), a feature level fusion technique that incorporates the class associations in correlation analysis of the feature sets. DCA performs an effective feature fusion by maximizing the pair-wise correlations across the two feature sets, and at the same time, eliminating the between-class correlations and restricting the correlations to be within classes.

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Authors:
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi
Submitted On:
16 July 2016 - 11:13pm
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DCA_ICASSP16_Poster.pdf

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[1] Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi, "Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/828. Accessed: Feb. 25, 2017.
@article{828-16,
url = {http://sigport.org/828},
author = {Mohammad Haghighat; Mohamed Abdel-Mottaleb; Wadee Alhalabi },
publisher = {IEEE SigPort},
title = {Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics},
year = {2016} }
TY - EJOUR
T1 - Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics
AU - Mohammad Haghighat; Mohamed Abdel-Mottaleb; Wadee Alhalabi
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/828
ER -
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. (2016). Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics. IEEE SigPort. http://sigport.org/828
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi, 2016. Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics. Available at: http://sigport.org/828.
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. (2016). "Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics." Web.
1. Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/828

Target detection for depth imaging using sparse single-photon data


This paper presents a new Bayesian model and associated algorithm
for depth and intensity profiling using full waveforms from timecorrelated
single-photon counting (TCSPC) measurements when the
photon count in very low. The model represents each Lidar waveform
as an unknown constant background level, which is combined
in the presence of a target, to a known impulse response weighted
by the target intensity and finally corrupted by Poisson noise. The
joint target detection and depth imaging problem is expressed as a

Paper Details

Authors:
Yoann Altmann, Ximing Ren, Aongus McCarthy, Gerald S. Buller
Submitted On:
19 March 2016 - 7:21am
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Altmann_ICASSP_2015_poster.pdf

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[1] Yoann Altmann, Ximing Ren, Aongus McCarthy, Gerald S. Buller, "Target detection for depth imaging using sparse single-photon data", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/800. Accessed: Feb. 25, 2017.
@article{800-16,
url = {http://sigport.org/800},
author = {Yoann Altmann; Ximing Ren; Aongus McCarthy; Gerald S. Buller },
publisher = {IEEE SigPort},
title = {Target detection for depth imaging using sparse single-photon data},
year = {2016} }
TY - EJOUR
T1 - Target detection for depth imaging using sparse single-photon data
AU - Yoann Altmann; Ximing Ren; Aongus McCarthy; Gerald S. Buller
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/800
ER -
Yoann Altmann, Ximing Ren, Aongus McCarthy, Gerald S. Buller. (2016). Target detection for depth imaging using sparse single-photon data. IEEE SigPort. http://sigport.org/800
Yoann Altmann, Ximing Ren, Aongus McCarthy, Gerald S. Buller, 2016. Target detection for depth imaging using sparse single-photon data. Available at: http://sigport.org/800.
Yoann Altmann, Ximing Ren, Aongus McCarthy, Gerald S. Buller. (2016). "Target detection for depth imaging using sparse single-photon data." Web.
1. Yoann Altmann, Ximing Ren, Aongus McCarthy, Gerald S. Buller. Target detection for depth imaging using sparse single-photon data [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/800

Super-Resolution DoA Estimation via Continuous Group Sparsity in The Covariance Domain

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Authors:
Cheng-Yu Hung, Mostafa Kaveh
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12 March 2016 - 1:41am
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icassp16-poster_landscape_final.pdf

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[1] Cheng-Yu Hung, Mostafa Kaveh, "Super-Resolution DoA Estimation via Continuous Group Sparsity in The Covariance Domain", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/627. Accessed: Feb. 25, 2017.
@article{627-16,
url = {http://sigport.org/627},
author = {Cheng-Yu Hung; Mostafa Kaveh },
publisher = {IEEE SigPort},
title = {Super-Resolution DoA Estimation via Continuous Group Sparsity in The Covariance Domain},
year = {2016} }
TY - EJOUR
T1 - Super-Resolution DoA Estimation via Continuous Group Sparsity in The Covariance Domain
AU - Cheng-Yu Hung; Mostafa Kaveh
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/627
ER -
Cheng-Yu Hung, Mostafa Kaveh. (2016). Super-Resolution DoA Estimation via Continuous Group Sparsity in The Covariance Domain. IEEE SigPort. http://sigport.org/627
Cheng-Yu Hung, Mostafa Kaveh, 2016. Super-Resolution DoA Estimation via Continuous Group Sparsity in The Covariance Domain. Available at: http://sigport.org/627.
Cheng-Yu Hung, Mostafa Kaveh. (2016). "Super-Resolution DoA Estimation via Continuous Group Sparsity in The Covariance Domain." Web.
1. Cheng-Yu Hung, Mostafa Kaveh. Super-Resolution DoA Estimation via Continuous Group Sparsity in The Covariance Domain [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/627

Time Delay Estimation: Applications and Algorithms


Time delay estimation refers to finding the time-differences-of-arrival between signals received at an array of sensors. In this presentation, representative applications of time delay estimation are first described. Algorithms for accurately estimating the time difference between two sensor outputs using random and deterministic signals are then presented and analyzed.

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23 February 2016 - 1:44pm
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[1] , "Time Delay Estimation: Applications and Algorithms", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/565. Accessed: Feb. 25, 2017.
@article{565-15,
url = {http://sigport.org/565},
author = { },
publisher = {IEEE SigPort},
title = {Time Delay Estimation: Applications and Algorithms},
year = {2015} }
TY - EJOUR
T1 - Time Delay Estimation: Applications and Algorithms
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/565
ER -
. (2015). Time Delay Estimation: Applications and Algorithms. IEEE SigPort. http://sigport.org/565
, 2015. Time Delay Estimation: Applications and Algorithms. Available at: http://sigport.org/565.
. (2015). "Time Delay Estimation: Applications and Algorithms." Web.
1. . Time Delay Estimation: Applications and Algorithms [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/565

A Parameter-Free MAP Image Reconstruction Algorithm for Impulse-Based UWB Ground Penetrating Radar

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Authors:
John M.M. Anderson , Lam Nguyen
Submitted On:
23 February 2016 - 1:44pm
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GlobalSIP2015_HowardUniversity.pdf

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[1] John M.M. Anderson , Lam Nguyen, "A Parameter-Free MAP Image Reconstruction Algorithm for Impulse-Based UWB Ground Penetrating Radar", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/531. Accessed: Feb. 25, 2017.
@article{531-15,
url = {http://sigport.org/531},
author = {John M.M. Anderson ; Lam Nguyen },
publisher = {IEEE SigPort},
title = {A Parameter-Free MAP Image Reconstruction Algorithm for Impulse-Based UWB Ground Penetrating Radar},
year = {2015} }
TY - EJOUR
T1 - A Parameter-Free MAP Image Reconstruction Algorithm for Impulse-Based UWB Ground Penetrating Radar
AU - John M.M. Anderson ; Lam Nguyen
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/531
ER -
John M.M. Anderson , Lam Nguyen. (2015). A Parameter-Free MAP Image Reconstruction Algorithm for Impulse-Based UWB Ground Penetrating Radar. IEEE SigPort. http://sigport.org/531
John M.M. Anderson , Lam Nguyen, 2015. A Parameter-Free MAP Image Reconstruction Algorithm for Impulse-Based UWB Ground Penetrating Radar. Available at: http://sigport.org/531.
John M.M. Anderson , Lam Nguyen. (2015). "A Parameter-Free MAP Image Reconstruction Algorithm for Impulse-Based UWB Ground Penetrating Radar." Web.
1. John M.M. Anderson , Lam Nguyen. A Parameter-Free MAP Image Reconstruction Algorithm for Impulse-Based UWB Ground Penetrating Radar [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/531