Sorry, you need to enable JavaScript to visit this website.

Biomedical signal processing

QUALITY ASSESSMENT OF MPEG-4 AVC/H.264 AND HEVC COMPRESSED VIDEO IN A TELEMEDICINE CONTEXT

Paper Details

Authors:
Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux
Submitted On:
14 September 2017 - 7:54pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster Paper 2905 ICIP 2017

(4 downloads)

Keywords

Subscribe

[1] Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux, "QUALITY ASSESSMENT OF MPEG-4 AVC/H.264 AND HEVC COMPRESSED VIDEO IN A TELEMEDICINE CONTEXT", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2055. Accessed: Sep. 25, 2017.
@article{2055-17,
url = {http://sigport.org/2055},
author = {Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux },
publisher = {IEEE SigPort},
title = {QUALITY ASSESSMENT OF MPEG-4 AVC/H.264 AND HEVC COMPRESSED VIDEO IN A TELEMEDICINE CONTEXT},
year = {2017} }
TY - EJOUR
T1 - QUALITY ASSESSMENT OF MPEG-4 AVC/H.264 AND HEVC COMPRESSED VIDEO IN A TELEMEDICINE CONTEXT
AU - Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2055
ER -
Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux. (2017). QUALITY ASSESSMENT OF MPEG-4 AVC/H.264 AND HEVC COMPRESSED VIDEO IN A TELEMEDICINE CONTEXT. IEEE SigPort. http://sigport.org/2055
Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux, 2017. QUALITY ASSESSMENT OF MPEG-4 AVC/H.264 AND HEVC COMPRESSED VIDEO IN A TELEMEDICINE CONTEXT. Available at: http://sigport.org/2055.
Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux. (2017). "QUALITY ASSESSMENT OF MPEG-4 AVC/H.264 AND HEVC COMPRESSED VIDEO IN A TELEMEDICINE CONTEXT." Web.
1. Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux. QUALITY ASSESSMENT OF MPEG-4 AVC/H.264 AND HEVC COMPRESSED VIDEO IN A TELEMEDICINE CONTEXT [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2055

AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION


We consider the problem of fovea segmentation and develop
a technique for delineation of macular regions based on the
active-disc formalism that we recently introduced. The outlining
problem is posed as one of the optimization of a locally
defined contrast function using gradient-ascent maximization
with respect to the affine transformation parameters
that characterize the active disc. For automatic localization
of the fovea and initialization of the active disc, we
use the directional-derivative-based matched filter. We report

Paper Details

Authors:
Rittwik Adhikari, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula
Submitted On:
13 September 2017 - 6:51am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP_17_Presentation_HK.pdf

(10 downloads)

Keywords

Subscribe

[1] Rittwik Adhikari, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula, "AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1969. Accessed: Sep. 25, 2017.
@article{1969-17,
url = {http://sigport.org/1969},
author = {Rittwik Adhikari; Yogish Kamath; Rajani Jampala; Chandra Sekhar Seelamantula },
publisher = {IEEE SigPort},
title = {AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION},
year = {2017} }
TY - EJOUR
T1 - AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION
AU - Rittwik Adhikari; Yogish Kamath; Rajani Jampala; Chandra Sekhar Seelamantula
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1969
ER -
Rittwik Adhikari, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula. (2017). AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION. IEEE SigPort. http://sigport.org/1969
Rittwik Adhikari, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula, 2017. AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION. Available at: http://sigport.org/1969.
Rittwik Adhikari, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula. (2017). "AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION." Web.
1. Rittwik Adhikari, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula. AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1969

CSMSDL: A Common Sequential Dictionary Learning Algorithm for Multi-Subject fMRI Data Sets Analysis


Sequential dictionary learning algorithms has gained widespread acceptance in functional magnetic resonance imaging (fMRI) data analysis. However, many problems in fMRI data analysis involve the analysis of multiple-subject fMRI data sets and the existing algorithms do not extend naturally to this case. In this paper we propose an algorithm dedicated to multiple-subject fMRI data analysis. The algorithm is named SMSDL for sequential multi-subject dictionary learning and differs from existing dictionary learning algorithms in its dictionary update stage.

Paper Details

Authors:
Abd-Krim Seghouane, Asif Iqbal
Submitted On:
11 September 2017 - 10:10pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster for ICIP 2017

(9 downloads)

Keywords

Subscribe

[1] Abd-Krim Seghouane, Asif Iqbal, "CSMSDL: A Common Sequential Dictionary Learning Algorithm for Multi-Subject fMRI Data Sets Analysis", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1923. Accessed: Sep. 25, 2017.
@article{1923-17,
url = {http://sigport.org/1923},
author = {Abd-Krim Seghouane; Asif Iqbal },
publisher = {IEEE SigPort},
title = {CSMSDL: A Common Sequential Dictionary Learning Algorithm for Multi-Subject fMRI Data Sets Analysis},
year = {2017} }
TY - EJOUR
T1 - CSMSDL: A Common Sequential Dictionary Learning Algorithm for Multi-Subject fMRI Data Sets Analysis
AU - Abd-Krim Seghouane; Asif Iqbal
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1923
ER -
Abd-Krim Seghouane, Asif Iqbal. (2017). CSMSDL: A Common Sequential Dictionary Learning Algorithm for Multi-Subject fMRI Data Sets Analysis. IEEE SigPort. http://sigport.org/1923
Abd-Krim Seghouane, Asif Iqbal, 2017. CSMSDL: A Common Sequential Dictionary Learning Algorithm for Multi-Subject fMRI Data Sets Analysis. Available at: http://sigport.org/1923.
Abd-Krim Seghouane, Asif Iqbal. (2017). "CSMSDL: A Common Sequential Dictionary Learning Algorithm for Multi-Subject fMRI Data Sets Analysis." Web.
1. Abd-Krim Seghouane, Asif Iqbal. CSMSDL: A Common Sequential Dictionary Learning Algorithm for Multi-Subject fMRI Data Sets Analysis [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1923

RESPIRATORY AIRFLOW ESTIMATION FROM LUNG SOUNDS BASED ON REGRESSION

Paper Details

Authors:
Elmar Messner, Martin Hagmüller, Paul Swatek, Freyja-Maria Smolle-Jüttner, Franz Pernkopf
Submitted On:
20 March 2017 - 12:25pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

poster.pdf

(244 downloads)

Keywords

Subscribe

[1] Elmar Messner, Martin Hagmüller, Paul Swatek, Freyja-Maria Smolle-Jüttner, Franz Pernkopf, "RESPIRATORY AIRFLOW ESTIMATION FROM LUNG SOUNDS BASED ON REGRESSION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1778. Accessed: Sep. 25, 2017.
@article{1778-17,
url = {http://sigport.org/1778},
author = {Elmar Messner; Martin Hagmüller; Paul Swatek; Freyja-Maria Smolle-Jüttner; Franz Pernkopf },
publisher = {IEEE SigPort},
title = {RESPIRATORY AIRFLOW ESTIMATION FROM LUNG SOUNDS BASED ON REGRESSION},
year = {2017} }
TY - EJOUR
T1 - RESPIRATORY AIRFLOW ESTIMATION FROM LUNG SOUNDS BASED ON REGRESSION
AU - Elmar Messner; Martin Hagmüller; Paul Swatek; Freyja-Maria Smolle-Jüttner; Franz Pernkopf
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1778
ER -
Elmar Messner, Martin Hagmüller, Paul Swatek, Freyja-Maria Smolle-Jüttner, Franz Pernkopf. (2017). RESPIRATORY AIRFLOW ESTIMATION FROM LUNG SOUNDS BASED ON REGRESSION. IEEE SigPort. http://sigport.org/1778
Elmar Messner, Martin Hagmüller, Paul Swatek, Freyja-Maria Smolle-Jüttner, Franz Pernkopf, 2017. RESPIRATORY AIRFLOW ESTIMATION FROM LUNG SOUNDS BASED ON REGRESSION. Available at: http://sigport.org/1778.
Elmar Messner, Martin Hagmüller, Paul Swatek, Freyja-Maria Smolle-Jüttner, Franz Pernkopf. (2017). "RESPIRATORY AIRFLOW ESTIMATION FROM LUNG SOUNDS BASED ON REGRESSION." Web.
1. Elmar Messner, Martin Hagmüller, Paul Swatek, Freyja-Maria Smolle-Jüttner, Franz Pernkopf. RESPIRATORY AIRFLOW ESTIMATION FROM LUNG SOUNDS BASED ON REGRESSION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1778

Non-Convex Sparse Optimization for Photon-Limited Imaging


While convex optimization for low-light imaging has received some attention by the imaging community, non-convex optimization techniques for photon-limited imaging are still in their nascent stages. In this thesis, we developed a stage-based non-convex approach to recover high-resolution sparse signals from low-dimensional measurements corrupted by Poisson noise. We incorporate gradient-based information to construct a sequence of quadratic subproblems with an $\ell_p$-norm ($0 \leq p < 1$) penalty term to promote sparsity.

PhDForum.pdf

PDF icon PhDForum.pdf (82 downloads)

Paper Details

Authors:
Lasith Adhikari, Roummel Marcia
Submitted On:
6 March 2017 - 10:40am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

PhDForum.pdf

(82 downloads)

Keywords

Additional Categories

Subscribe

[1] Lasith Adhikari, Roummel Marcia, "Non-Convex Sparse Optimization for Photon-Limited Imaging", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1650. Accessed: Sep. 25, 2017.
@article{1650-17,
url = {http://sigport.org/1650},
author = {Lasith Adhikari; Roummel Marcia },
publisher = {IEEE SigPort},
title = {Non-Convex Sparse Optimization for Photon-Limited Imaging},
year = {2017} }
TY - EJOUR
T1 - Non-Convex Sparse Optimization for Photon-Limited Imaging
AU - Lasith Adhikari; Roummel Marcia
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1650
ER -
Lasith Adhikari, Roummel Marcia. (2017). Non-Convex Sparse Optimization for Photon-Limited Imaging. IEEE SigPort. http://sigport.org/1650
Lasith Adhikari, Roummel Marcia, 2017. Non-Convex Sparse Optimization for Photon-Limited Imaging. Available at: http://sigport.org/1650.
Lasith Adhikari, Roummel Marcia. (2017). "Non-Convex Sparse Optimization for Photon-Limited Imaging." Web.
1. Lasith Adhikari, Roummel Marcia. Non-Convex Sparse Optimization for Photon-Limited Imaging [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1650

Reduction of Necessary Data Rate for Neural Data Through Exponential and Sinusoidal Spline Decomposition using the Finite Rate of Innovation Framework


The sampling of neural signals plays an important role in modern neuroscience, especially for prosthetics. However, due to hardware and data rate constraints, only spike trains can get recovered reliably. State of the art prosthetics can still achieve impressive results, but to get higher resolutions the used data rate needs to be reduced. In this paper, this is done by expressing the data with exponential and sinusoidal splines.

Paper Details

Authors:
Submitted On:
3 March 2017 - 6:30am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

FRIVortrag.pdf

(58 downloads)

FRIVortrag.pdf

(61 downloads)

Keywords

Subscribe

[1] , "Reduction of Necessary Data Rate for Neural Data Through Exponential and Sinusoidal Spline Decomposition using the Finite Rate of Innovation Framework", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1605. Accessed: Sep. 25, 2017.
@article{1605-17,
url = {http://sigport.org/1605},
author = { },
publisher = {IEEE SigPort},
title = {Reduction of Necessary Data Rate for Neural Data Through Exponential and Sinusoidal Spline Decomposition using the Finite Rate of Innovation Framework},
year = {2017} }
TY - EJOUR
T1 - Reduction of Necessary Data Rate for Neural Data Through Exponential and Sinusoidal Spline Decomposition using the Finite Rate of Innovation Framework
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1605
ER -
. (2017). Reduction of Necessary Data Rate for Neural Data Through Exponential and Sinusoidal Spline Decomposition using the Finite Rate of Innovation Framework. IEEE SigPort. http://sigport.org/1605
, 2017. Reduction of Necessary Data Rate for Neural Data Through Exponential and Sinusoidal Spline Decomposition using the Finite Rate of Innovation Framework. Available at: http://sigport.org/1605.
. (2017). "Reduction of Necessary Data Rate for Neural Data Through Exponential and Sinusoidal Spline Decomposition using the Finite Rate of Innovation Framework." Web.
1. . Reduction of Necessary Data Rate for Neural Data Through Exponential and Sinusoidal Spline Decomposition using the Finite Rate of Innovation Framework [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1605

EVENT-RELATED SYNCHRONISATION RESPONSES TO N-BACK MEMORY TASKS DISCRIMINATE BETWEEN HEALTHY AGEING, MILD COGNITIVE IMPAIRMENT, AND MILD ALZHEIMER’S DISEASE


In this study we investigate whether or not event-related (de)synchronisation (ERD/ERS) can be used to differenti- ate between 27 healthy elderly, 21 subjects diagnosed with amnestic mild cognitive impairment (aMCI) and 16 mild Alzheimer’s disease (AD) patients. Using 32-channel EEG recordings, we measured ERD responses to a three-level vi- sual N-back task (N = 0, 1, 2) on the well-known delta, theta, alpha, beta and gamma bands.

Paper Details

Authors:
Francisco J. Fraga, Leonardo A. Ferreira, Tiago H. Falk, Erin Johns, Natalie D. Phillips
Submitted On:
2 March 2017 - 7:08am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICASSP 2017 Paper #3050 (Francisco J Fraga) - ERD responses to N-back tasks discriminate MCI from Healthy and AD patients

(81 downloads)

Keywords

Subscribe

[1] Francisco J. Fraga, Leonardo A. Ferreira, Tiago H. Falk, Erin Johns, Natalie D. Phillips, "EVENT-RELATED SYNCHRONISATION RESPONSES TO N-BACK MEMORY TASKS DISCRIMINATE BETWEEN HEALTHY AGEING, MILD COGNITIVE IMPAIRMENT, AND MILD ALZHEIMER’S DISEASE", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1582. Accessed: Sep. 25, 2017.
@article{1582-17,
url = {http://sigport.org/1582},
author = {Francisco J. Fraga; Leonardo A. Ferreira; Tiago H. Falk; Erin Johns; Natalie D. Phillips },
publisher = {IEEE SigPort},
title = {EVENT-RELATED SYNCHRONISATION RESPONSES TO N-BACK MEMORY TASKS DISCRIMINATE BETWEEN HEALTHY AGEING, MILD COGNITIVE IMPAIRMENT, AND MILD ALZHEIMER’S DISEASE},
year = {2017} }
TY - EJOUR
T1 - EVENT-RELATED SYNCHRONISATION RESPONSES TO N-BACK MEMORY TASKS DISCRIMINATE BETWEEN HEALTHY AGEING, MILD COGNITIVE IMPAIRMENT, AND MILD ALZHEIMER’S DISEASE
AU - Francisco J. Fraga; Leonardo A. Ferreira; Tiago H. Falk; Erin Johns; Natalie D. Phillips
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1582
ER -
Francisco J. Fraga, Leonardo A. Ferreira, Tiago H. Falk, Erin Johns, Natalie D. Phillips. (2017). EVENT-RELATED SYNCHRONISATION RESPONSES TO N-BACK MEMORY TASKS DISCRIMINATE BETWEEN HEALTHY AGEING, MILD COGNITIVE IMPAIRMENT, AND MILD ALZHEIMER’S DISEASE. IEEE SigPort. http://sigport.org/1582
Francisco J. Fraga, Leonardo A. Ferreira, Tiago H. Falk, Erin Johns, Natalie D. Phillips, 2017. EVENT-RELATED SYNCHRONISATION RESPONSES TO N-BACK MEMORY TASKS DISCRIMINATE BETWEEN HEALTHY AGEING, MILD COGNITIVE IMPAIRMENT, AND MILD ALZHEIMER’S DISEASE. Available at: http://sigport.org/1582.
Francisco J. Fraga, Leonardo A. Ferreira, Tiago H. Falk, Erin Johns, Natalie D. Phillips. (2017). "EVENT-RELATED SYNCHRONISATION RESPONSES TO N-BACK MEMORY TASKS DISCRIMINATE BETWEEN HEALTHY AGEING, MILD COGNITIVE IMPAIRMENT, AND MILD ALZHEIMER’S DISEASE." Web.
1. Francisco J. Fraga, Leonardo A. Ferreira, Tiago H. Falk, Erin Johns, Natalie D. Phillips. EVENT-RELATED SYNCHRONISATION RESPONSES TO N-BACK MEMORY TASKS DISCRIMINATE BETWEEN HEALTHY AGEING, MILD COGNITIVE IMPAIRMENT, AND MILD ALZHEIMER’S DISEASE [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1582

COMPRESSIVE SENSING BASED ECG MONITORING WITH EFFECTIVE AF DETECTION


Atrial fibrillation (AF) patients need long-term electrocardiography (ECG) monitoring to detect occurrence of AF. We can acquire ECG signals under low power by compressive sensing based sensor and detect AF by existing algorithms. However, the compression ratio of AF signal is low when DWT basis is applied for CS reconstruction. On the other hand the complexity of AF detection algorithms is high. In this paper, we propose a CS-based ECG monitoring system with effective AF detection. We exploit dictionary learning to improve 2.5x better compression ratio than existing works.

Paper Details

Authors:
Hung-Chi Kuo, Yu-Min Lin and An-Yeu (Andy) Wu
Submitted On:
1 March 2017 - 1:50am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster_1877_Kuo.pdf

(88 downloads)

Keywords

Subscribe

[1] Hung-Chi Kuo, Yu-Min Lin and An-Yeu (Andy) Wu, " COMPRESSIVE SENSING BASED ECG MONITORING WITH EFFECTIVE AF DETECTION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1534. Accessed: Sep. 25, 2017.
@article{1534-17,
url = {http://sigport.org/1534},
author = {Hung-Chi Kuo; Yu-Min Lin and An-Yeu (Andy) Wu },
publisher = {IEEE SigPort},
title = { COMPRESSIVE SENSING BASED ECG MONITORING WITH EFFECTIVE AF DETECTION},
year = {2017} }
TY - EJOUR
T1 - COMPRESSIVE SENSING BASED ECG MONITORING WITH EFFECTIVE AF DETECTION
AU - Hung-Chi Kuo; Yu-Min Lin and An-Yeu (Andy) Wu
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1534
ER -
Hung-Chi Kuo, Yu-Min Lin and An-Yeu (Andy) Wu. (2017). COMPRESSIVE SENSING BASED ECG MONITORING WITH EFFECTIVE AF DETECTION. IEEE SigPort. http://sigport.org/1534
Hung-Chi Kuo, Yu-Min Lin and An-Yeu (Andy) Wu, 2017. COMPRESSIVE SENSING BASED ECG MONITORING WITH EFFECTIVE AF DETECTION. Available at: http://sigport.org/1534.
Hung-Chi Kuo, Yu-Min Lin and An-Yeu (Andy) Wu. (2017). " COMPRESSIVE SENSING BASED ECG MONITORING WITH EFFECTIVE AF DETECTION." Web.
1. Hung-Chi Kuo, Yu-Min Lin and An-Yeu (Andy) Wu. COMPRESSIVE SENSING BASED ECG MONITORING WITH EFFECTIVE AF DETECTION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1534

EEG CHANNEL OPTIMIZATION VIA SPARSE COMMON SPATIAL FILTER


In this paper, we propose a novel sparse common spatial pattern (CSP) algorithm to optimally select channels of EEG signals. Compared to the traditional CSP, which maximizes the variance of signals in one class and minimizes the variance of signals in the other class,the classification accuracy is guaranteed by a constraint that the ratio
of variances of signals in two different classes is lower bounded.Then, a sparse spatial filter is achieved by minimizing the l1-norm of filter coefficients and channels of EEG signals can be further optimized.

Paper Details

Authors:
Submitted On:
11 March 2017 - 8:49pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster-ICASSP.pdf

(52 downloads)

Keywords

Subscribe

[1] , "EEG CHANNEL OPTIMIZATION VIA SPARSE COMMON SPATIAL FILTER", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1518. Accessed: Sep. 25, 2017.
@article{1518-17,
url = {http://sigport.org/1518},
author = { },
publisher = {IEEE SigPort},
title = {EEG CHANNEL OPTIMIZATION VIA SPARSE COMMON SPATIAL FILTER},
year = {2017} }
TY - EJOUR
T1 - EEG CHANNEL OPTIMIZATION VIA SPARSE COMMON SPATIAL FILTER
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1518
ER -
. (2017). EEG CHANNEL OPTIMIZATION VIA SPARSE COMMON SPATIAL FILTER. IEEE SigPort. http://sigport.org/1518
, 2017. EEG CHANNEL OPTIMIZATION VIA SPARSE COMMON SPATIAL FILTER. Available at: http://sigport.org/1518.
. (2017). "EEG CHANNEL OPTIMIZATION VIA SPARSE COMMON SPATIAL FILTER." Web.
1. . EEG CHANNEL OPTIMIZATION VIA SPARSE COMMON SPATIAL FILTER [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1518

Fast and Stable Signal Deconvolution via Compressible State-Space Models


Objective: Common biological measurements are in
the form of noisy convolutions of signals of interest with possibly
unknown and transient blurring kernels. Examples include EEG
and calcium imaging data. Thus, signal deconvolution of these
measurements is crucial in understanding the underlying biological
processes. The objective of this paper is to develop fast and
stable solutions for signal deconvolution from noisy, blurred and
undersampled data, where the signals are in the form of discrete

Paper Details

Authors:
Abbas Kazemipour, Ji Liu, Min Wu , Patrick Kanold and Behtash Babadi
Submitted On:
12 December 2016 - 9:35am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

FCSS_slides.pdf

(153 downloads)

Keywords

Additional Categories

Subscribe

[1] Abbas Kazemipour, Ji Liu, Min Wu , Patrick Kanold and Behtash Babadi, "Fast and Stable Signal Deconvolution via Compressible State-Space Models", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1438. Accessed: Sep. 25, 2017.
@article{1438-16,
url = {http://sigport.org/1438},
author = {Abbas Kazemipour; Ji Liu; Min Wu ; Patrick Kanold and Behtash Babadi },
publisher = {IEEE SigPort},
title = {Fast and Stable Signal Deconvolution via Compressible State-Space Models},
year = {2016} }
TY - EJOUR
T1 - Fast and Stable Signal Deconvolution via Compressible State-Space Models
AU - Abbas Kazemipour; Ji Liu; Min Wu ; Patrick Kanold and Behtash Babadi
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1438
ER -
Abbas Kazemipour, Ji Liu, Min Wu , Patrick Kanold and Behtash Babadi. (2016). Fast and Stable Signal Deconvolution via Compressible State-Space Models. IEEE SigPort. http://sigport.org/1438
Abbas Kazemipour, Ji Liu, Min Wu , Patrick Kanold and Behtash Babadi, 2016. Fast and Stable Signal Deconvolution via Compressible State-Space Models. Available at: http://sigport.org/1438.
Abbas Kazemipour, Ji Liu, Min Wu , Patrick Kanold and Behtash Babadi. (2016). "Fast and Stable Signal Deconvolution via Compressible State-Space Models." Web.
1. Abbas Kazemipour, Ji Liu, Min Wu , Patrick Kanold and Behtash Babadi. Fast and Stable Signal Deconvolution via Compressible State-Space Models [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1438

Pages