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Biomedical signal processing

Analysis of p-norm Regularized Subproblem Minimization for Sparse Photon-Limited Image Recovery


Critical to accurate reconstruction of sparse signals from low-dimensional low-photon count observations is the solution of nonlinear optimization problems that promote sparse solutions. In this work, we explore recovering high-resolution sparse signals from low-resolution measurements corrupted by Poisson noise using a gradient-based optimization approach with non-convex regularization. In particular, we analyze zero-finding methods for solving the p-norm regularized minimization subproblems arising from a sequential quadratic approach.

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Authors:
Aramayis Orkusyan, Lasith Adhikari, Joanna Valenzuela, Roummel F. Marcia
Submitted On:
16 March 2016 - 2:44pm
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ICASSP2016.pdf

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[1] Aramayis Orkusyan, Lasith Adhikari, Joanna Valenzuela, Roummel F. Marcia, "Analysis of p-norm Regularized Subproblem Minimization for Sparse Photon-Limited Image Recovery", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/724. Accessed: Apr. 26, 2019.
@article{724-16,
url = {http://sigport.org/724},
author = {Aramayis Orkusyan; Lasith Adhikari; Joanna Valenzuela; Roummel F. Marcia },
publisher = {IEEE SigPort},
title = {Analysis of p-norm Regularized Subproblem Minimization for Sparse Photon-Limited Image Recovery},
year = {2016} }
TY - EJOUR
T1 - Analysis of p-norm Regularized Subproblem Minimization for Sparse Photon-Limited Image Recovery
AU - Aramayis Orkusyan; Lasith Adhikari; Joanna Valenzuela; Roummel F. Marcia
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/724
ER -
Aramayis Orkusyan, Lasith Adhikari, Joanna Valenzuela, Roummel F. Marcia. (2016). Analysis of p-norm Regularized Subproblem Minimization for Sparse Photon-Limited Image Recovery. IEEE SigPort. http://sigport.org/724
Aramayis Orkusyan, Lasith Adhikari, Joanna Valenzuela, Roummel F. Marcia, 2016. Analysis of p-norm Regularized Subproblem Minimization for Sparse Photon-Limited Image Recovery. Available at: http://sigport.org/724.
Aramayis Orkusyan, Lasith Adhikari, Joanna Valenzuela, Roummel F. Marcia. (2016). "Analysis of p-norm Regularized Subproblem Minimization for Sparse Photon-Limited Image Recovery." Web.
1. Aramayis Orkusyan, Lasith Adhikari, Joanna Valenzuela, Roummel F. Marcia. Analysis of p-norm Regularized Subproblem Minimization for Sparse Photon-Limited Image Recovery [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/724

An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning For Long-Term Wireless Health Monitoring

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Authors:
Kai XU, Yixing Li, Fengbo Ren
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19 March 2016 - 9:03pm
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ICASSP poster.pdf

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[1] Kai XU, Yixing Li, Fengbo Ren, "An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning For Long-Term Wireless Health Monitoring ", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/703. Accessed: Apr. 26, 2019.
@article{703-16,
url = {http://sigport.org/703},
author = {Kai XU; Yixing Li; Fengbo Ren },
publisher = {IEEE SigPort},
title = {An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning For Long-Term Wireless Health Monitoring },
year = {2016} }
TY - EJOUR
T1 - An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning For Long-Term Wireless Health Monitoring
AU - Kai XU; Yixing Li; Fengbo Ren
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/703
ER -
Kai XU, Yixing Li, Fengbo Ren. (2016). An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning For Long-Term Wireless Health Monitoring . IEEE SigPort. http://sigport.org/703
Kai XU, Yixing Li, Fengbo Ren, 2016. An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning For Long-Term Wireless Health Monitoring . Available at: http://sigport.org/703.
Kai XU, Yixing Li, Fengbo Ren. (2016). "An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning For Long-Term Wireless Health Monitoring ." Web.
1. Kai XU, Yixing Li, Fengbo Ren. An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning For Long-Term Wireless Health Monitoring [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/703

FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG

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Authors:
Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.BrandonWestover
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13 March 2016 - 12:18pm
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ICASSP2016Poster_Elham_landscape_2.pdf

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[1] Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.BrandonWestover, "FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/655. Accessed: Apr. 26, 2019.
@article{655-16,
url = {http://sigport.org/655},
author = {Elham Bagheri; Jing Jin; Justin Dauwels; Sydney Cash; M.BrandonWestover },
publisher = {IEEE SigPort},
title = {FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG},
year = {2016} }
TY - EJOUR
T1 - FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG
AU - Elham Bagheri; Jing Jin; Justin Dauwels; Sydney Cash; M.BrandonWestover
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/655
ER -
Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.BrandonWestover. (2016). FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG. IEEE SigPort. http://sigport.org/655
Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.BrandonWestover, 2016. FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG. Available at: http://sigport.org/655.
Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.BrandonWestover. (2016). "FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG." Web.
1. Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.BrandonWestover. FAST AND EFFICIENT REJECTION OF BACKGROUND WAVEFORMS IN INTERICTAL EEG [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/655

EPILEPTIFORM SPIKE TEMPLATE SELECTION USING DYNAMIC TIME WARPING AND AFFINITY PROPAGATION

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Authors:
John Thomas, Jing Jin, Justin Dauwels, Sydney S. Cash, M. Brandon Westover
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13 March 2016 - 12:15pm
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ICASSP_John.pdf

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[1] John Thomas, Jing Jin, Justin Dauwels, Sydney S. Cash, M. Brandon Westover, "EPILEPTIFORM SPIKE TEMPLATE SELECTION USING DYNAMIC TIME WARPING AND AFFINITY PROPAGATION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/654. Accessed: Apr. 26, 2019.
@article{654-16,
url = {http://sigport.org/654},
author = {John Thomas; Jing Jin; Justin Dauwels; Sydney S. Cash; M. Brandon Westover },
publisher = {IEEE SigPort},
title = {EPILEPTIFORM SPIKE TEMPLATE SELECTION USING DYNAMIC TIME WARPING AND AFFINITY PROPAGATION},
year = {2016} }
TY - EJOUR
T1 - EPILEPTIFORM SPIKE TEMPLATE SELECTION USING DYNAMIC TIME WARPING AND AFFINITY PROPAGATION
AU - John Thomas; Jing Jin; Justin Dauwels; Sydney S. Cash; M. Brandon Westover
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/654
ER -
John Thomas, Jing Jin, Justin Dauwels, Sydney S. Cash, M. Brandon Westover. (2016). EPILEPTIFORM SPIKE TEMPLATE SELECTION USING DYNAMIC TIME WARPING AND AFFINITY PROPAGATION. IEEE SigPort. http://sigport.org/654
John Thomas, Jing Jin, Justin Dauwels, Sydney S. Cash, M. Brandon Westover, 2016. EPILEPTIFORM SPIKE TEMPLATE SELECTION USING DYNAMIC TIME WARPING AND AFFINITY PROPAGATION. Available at: http://sigport.org/654.
John Thomas, Jing Jin, Justin Dauwels, Sydney S. Cash, M. Brandon Westover. (2016). "EPILEPTIFORM SPIKE TEMPLATE SELECTION USING DYNAMIC TIME WARPING AND AFFINITY PROPAGATION." Web.
1. John Thomas, Jing Jin, Justin Dauwels, Sydney S. Cash, M. Brandon Westover. EPILEPTIFORM SPIKE TEMPLATE SELECTION USING DYNAMIC TIME WARPING AND AFFINITY PROPAGATION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/654

TRANSIENT MODEL OF EEG USING GINI INDEX-BASED MATCHING PURSUIT


EEG Model

We introduce a novel, transient model for the electroencephalogram (EEG) as the noisy addition of linear filters responding to trains of delta functions. We set the synthesis part as a parameter-tuning problem and obtain synthetic EEG-like data that visually resembles brain activity in the time and frequency domains. For the analysis counterpart, we use sparse approximation to decompose the signal in relevant events via Matching Pursuit.

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Authors:
Carlos A Loza, Jose C Principe
Submitted On:
12 March 2016 - 10:35am
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ICASSP2016_Loza_Principe_poster.pdf

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[1] Carlos A Loza, Jose C Principe, "TRANSIENT MODEL OF EEG USING GINI INDEX-BASED MATCHING PURSUIT", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/643. Accessed: Apr. 26, 2019.
@article{643-16,
url = {http://sigport.org/643},
author = {Carlos A Loza; Jose C Principe },
publisher = {IEEE SigPort},
title = {TRANSIENT MODEL OF EEG USING GINI INDEX-BASED MATCHING PURSUIT},
year = {2016} }
TY - EJOUR
T1 - TRANSIENT MODEL OF EEG USING GINI INDEX-BASED MATCHING PURSUIT
AU - Carlos A Loza; Jose C Principe
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/643
ER -
Carlos A Loza, Jose C Principe. (2016). TRANSIENT MODEL OF EEG USING GINI INDEX-BASED MATCHING PURSUIT. IEEE SigPort. http://sigport.org/643
Carlos A Loza, Jose C Principe, 2016. TRANSIENT MODEL OF EEG USING GINI INDEX-BASED MATCHING PURSUIT. Available at: http://sigport.org/643.
Carlos A Loza, Jose C Principe. (2016). "TRANSIENT MODEL OF EEG USING GINI INDEX-BASED MATCHING PURSUIT." Web.
1. Carlos A Loza, Jose C Principe. TRANSIENT MODEL OF EEG USING GINI INDEX-BASED MATCHING PURSUIT [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/643

EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS

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Authors:
Alexander R. Johansen, Jing Jin, Tomasz Maszczyk, Justin Dauwels, Sydney S. Cash, M. Brandon Westover
Submitted On:
12 March 2016 - 8:31am
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ICASSP2016Poster_CNN.pdf

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[1] Alexander R. Johansen, Jing Jin, Tomasz Maszczyk, Justin Dauwels, Sydney S. Cash, M. Brandon Westover, "EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/639. Accessed: Apr. 26, 2019.
@article{639-16,
url = {http://sigport.org/639},
author = {Alexander R. Johansen; Jing Jin; Tomasz Maszczyk; Justin Dauwels; Sydney S. Cash; M. Brandon Westover },
publisher = {IEEE SigPort},
title = {EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS},
year = {2016} }
TY - EJOUR
T1 - EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS
AU - Alexander R. Johansen; Jing Jin; Tomasz Maszczyk; Justin Dauwels; Sydney S. Cash; M. Brandon Westover
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/639
ER -
Alexander R. Johansen, Jing Jin, Tomasz Maszczyk, Justin Dauwels, Sydney S. Cash, M. Brandon Westover. (2016). EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS. IEEE SigPort. http://sigport.org/639
Alexander R. Johansen, Jing Jin, Tomasz Maszczyk, Justin Dauwels, Sydney S. Cash, M. Brandon Westover, 2016. EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS. Available at: http://sigport.org/639.
Alexander R. Johansen, Jing Jin, Tomasz Maszczyk, Justin Dauwels, Sydney S. Cash, M. Brandon Westover. (2016). "EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS." Web.
1. Alexander R. Johansen, Jing Jin, Tomasz Maszczyk, Justin Dauwels, Sydney S. Cash, M. Brandon Westover. EPILEPTIFORM SPIKE DETECTION VIA CONVOLUTIONAL NEURAL NETWORKS [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/639

Brain Functional Connectivity Analysis Using Mutual Information

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Authors:
Zhe Wang, Ahmed Alahmadi, David Zhu
Submitted On:
23 February 2016 - 1:44pm
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[1] Zhe Wang, Ahmed Alahmadi, David Zhu, "Brain Functional Connectivity Analysis Using Mutual Information", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/549. Accessed: Apr. 26, 2019.
@article{549-15,
url = {http://sigport.org/549},
author = {Zhe Wang; Ahmed Alahmadi; David Zhu },
publisher = {IEEE SigPort},
title = {Brain Functional Connectivity Analysis Using Mutual Information},
year = {2015} }
TY - EJOUR
T1 - Brain Functional Connectivity Analysis Using Mutual Information
AU - Zhe Wang; Ahmed Alahmadi; David Zhu
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/549
ER -
Zhe Wang, Ahmed Alahmadi, David Zhu. (2015). Brain Functional Connectivity Analysis Using Mutual Information. IEEE SigPort. http://sigport.org/549
Zhe Wang, Ahmed Alahmadi, David Zhu, 2015. Brain Functional Connectivity Analysis Using Mutual Information. Available at: http://sigport.org/549.
Zhe Wang, Ahmed Alahmadi, David Zhu. (2015). "Brain Functional Connectivity Analysis Using Mutual Information." Web.
1. Zhe Wang, Ahmed Alahmadi, David Zhu. Brain Functional Connectivity Analysis Using Mutual Information [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/549

Brain Functional Connectivity Analysis Using Mutual Information

Paper Details

Authors:
Zhe Wang, Ahmed Alahmadi, David Zhu
Submitted On:
23 February 2016 - 1:44pm
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presentation.pdf

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[1] Zhe Wang, Ahmed Alahmadi, David Zhu, "Brain Functional Connectivity Analysis Using Mutual Information", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/548. Accessed: Apr. 26, 2019.
@article{548-15,
url = {http://sigport.org/548},
author = {Zhe Wang; Ahmed Alahmadi; David Zhu },
publisher = {IEEE SigPort},
title = {Brain Functional Connectivity Analysis Using Mutual Information},
year = {2015} }
TY - EJOUR
T1 - Brain Functional Connectivity Analysis Using Mutual Information
AU - Zhe Wang; Ahmed Alahmadi; David Zhu
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/548
ER -
Zhe Wang, Ahmed Alahmadi, David Zhu. (2015). Brain Functional Connectivity Analysis Using Mutual Information. IEEE SigPort. http://sigport.org/548
Zhe Wang, Ahmed Alahmadi, David Zhu, 2015. Brain Functional Connectivity Analysis Using Mutual Information. Available at: http://sigport.org/548.
Zhe Wang, Ahmed Alahmadi, David Zhu. (2015). "Brain Functional Connectivity Analysis Using Mutual Information." Web.
1. Zhe Wang, Ahmed Alahmadi, David Zhu. Brain Functional Connectivity Analysis Using Mutual Information [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/548

Motor Imagery Classification Using Multiresolution Analysis and Sparse Representation of EEG Signals

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Authors:
George Atia, Alan Paris, Azadeh Vosoughi
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23 February 2016 - 1:44pm
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Global SIP Final.pdf

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[1] George Atia, Alan Paris, Azadeh Vosoughi, "Motor Imagery Classification Using Multiresolution Analysis and Sparse Representation of EEG Signals", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/520. Accessed: Apr. 26, 2019.
@article{520-15,
url = {http://sigport.org/520},
author = {George Atia; Alan Paris; Azadeh Vosoughi },
publisher = {IEEE SigPort},
title = {Motor Imagery Classification Using Multiresolution Analysis and Sparse Representation of EEG Signals},
year = {2015} }
TY - EJOUR
T1 - Motor Imagery Classification Using Multiresolution Analysis and Sparse Representation of EEG Signals
AU - George Atia; Alan Paris; Azadeh Vosoughi
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/520
ER -
George Atia, Alan Paris, Azadeh Vosoughi. (2015). Motor Imagery Classification Using Multiresolution Analysis and Sparse Representation of EEG Signals. IEEE SigPort. http://sigport.org/520
George Atia, Alan Paris, Azadeh Vosoughi, 2015. Motor Imagery Classification Using Multiresolution Analysis and Sparse Representation of EEG Signals. Available at: http://sigport.org/520.
George Atia, Alan Paris, Azadeh Vosoughi. (2015). "Motor Imagery Classification Using Multiresolution Analysis and Sparse Representation of EEG Signals." Web.
1. George Atia, Alan Paris, Azadeh Vosoughi. Motor Imagery Classification Using Multiresolution Analysis and Sparse Representation of EEG Signals [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/520

Subject Independent Affective States Classification Using EEG Signals


Affective states classification has become an important part of the Human-Computer Interface (HCI) study. In recent years, studies of physiological signals, such as ECG, GSR and EEG on affective expression have shown very promising results. In this study, we carried out two experiments to better understand the neurological expression of emotions through the use of EEG signals. In particular, we carried out a subject- independent affective states classification study using narrow- band spectral power of the EEG signals.

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Authors:
Konstantinos N. Plataniotis
Submitted On:
23 February 2016 - 1:44pm
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HaiyanXu_GlobalSIP2015.pdf

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[1] Konstantinos N. Plataniotis, "Subject Independent Affective States Classification Using EEG Signals", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/472. Accessed: Apr. 26, 2019.
@article{472-15,
url = {http://sigport.org/472},
author = {Konstantinos N. Plataniotis },
publisher = {IEEE SigPort},
title = {Subject Independent Affective States Classification Using EEG Signals},
year = {2015} }
TY - EJOUR
T1 - Subject Independent Affective States Classification Using EEG Signals
AU - Konstantinos N. Plataniotis
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/472
ER -
Konstantinos N. Plataniotis. (2015). Subject Independent Affective States Classification Using EEG Signals. IEEE SigPort. http://sigport.org/472
Konstantinos N. Plataniotis, 2015. Subject Independent Affective States Classification Using EEG Signals. Available at: http://sigport.org/472.
Konstantinos N. Plataniotis. (2015). "Subject Independent Affective States Classification Using EEG Signals." Web.
1. Konstantinos N. Plataniotis. Subject Independent Affective States Classification Using EEG Signals [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/472

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