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Biomedical signal processing

A Mobile EEG System for Practical Applications


In this study, we present a new 64-channel mobile EEG system (NeusenW, Neuracle Inc.), and compare it to a state-of-the-art wired laboratory EEG system and evaluate the EEG signal quality. Previous studies were only performed on seated participants in laboratory environments, and only a very limited number focus on motion conditions. In this study, we instead implemented experiments in standing, walking and running conditions.

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Authors:
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao
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13 November 2017 - 4:08pm
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[1] Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao, "A Mobile EEG System for Practical Applications", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2341. Accessed: Nov. 21, 2017.
@article{2341-17,
url = {http://sigport.org/2341},
author = {Xiaoshan Huang; Erwei Yin; Yijun Wang; Rami Saab; Xiaorong Gao },
publisher = {IEEE SigPort},
title = {A Mobile EEG System for Practical Applications},
year = {2017} }
TY - EJOUR
T1 - A Mobile EEG System for Practical Applications
AU - Xiaoshan Huang; Erwei Yin; Yijun Wang; Rami Saab; Xiaorong Gao
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2341
ER -
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. (2017). A Mobile EEG System for Practical Applications. IEEE SigPort. http://sigport.org/2341
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao, 2017. A Mobile EEG System for Practical Applications. Available at: http://sigport.org/2341.
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. (2017). "A Mobile EEG System for Practical Applications." Web.
1. Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. A Mobile EEG System for Practical Applications [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2341

OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES


Individuals with auditory neuropathy spectrum disorder (ANSD) or auditory processing disorders (APDs) often suffer from temporal processing deficits leading to degraded speech perception. The situation becomes worse in the presence of background noise. Evidence exists that the exaggeration of speech envelope may enhance intelligibility, although a comprehensive evaluation of envelope enhancement algorithms is lacking.

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10 November 2017 - 7:17pm
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[1] , "OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2301. Accessed: Nov. 21, 2017.
@article{2301-17,
url = {http://sigport.org/2301},
author = { },
publisher = {IEEE SigPort},
title = {OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES},
year = {2017} }
TY - EJOUR
T1 - OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2301
ER -
. (2017). OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES. IEEE SigPort. http://sigport.org/2301
, 2017. OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES. Available at: http://sigport.org/2301.
. (2017). "OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES." Web.
1. . OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2301

Heart Sound Segmentation using Switching Linear Dynamical Models


Localization of exact positions of the fundamental heart sounds (FHS) is an essential step towards automatic analysis of heart sound phonocardiogram (PCG) recordings, the automatic segmentation allows for data-driven classification of heart pathological events. Current approach using probabilistic models such as hidden Markov models (HMMs) has improved accuracy of heart sound segmentation.

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Authors:
Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu
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10 November 2017 - 10:14am
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[1] Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu, "Heart Sound Segmentation using Switching Linear Dynamical Models", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2293. Accessed: Nov. 21, 2017.
@article{2293-17,
url = {http://sigport.org/2293},
author = {Fuad Noman; Sh-Hussain Salleh; Chee-Ming Ting; Hadri Hu },
publisher = {IEEE SigPort},
title = {Heart Sound Segmentation using Switching Linear Dynamical Models},
year = {2017} }
TY - EJOUR
T1 - Heart Sound Segmentation using Switching Linear Dynamical Models
AU - Fuad Noman; Sh-Hussain Salleh; Chee-Ming Ting; Hadri Hu
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2293
ER -
Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu. (2017). Heart Sound Segmentation using Switching Linear Dynamical Models. IEEE SigPort. http://sigport.org/2293
Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu, 2017. Heart Sound Segmentation using Switching Linear Dynamical Models. Available at: http://sigport.org/2293.
Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu. (2017). "Heart Sound Segmentation using Switching Linear Dynamical Models." Web.
1. Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu. Heart Sound Segmentation using Switching Linear Dynamical Models [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2293

ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD


Afternoon sleepiness in daily life reduces arousal level, performance, and so on. It has been cleared that short naps are effective to cancel the sleepiness. Sleep stage 2 is one of important factors about sleeping especially in short time nap. Sleep spindles are especially important hallmarks of sleep stage 2. Therefore, it is necessary to find a spindle for analysis in sleep stage 2.

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Authors:
Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa
Submitted On:
12 November 2017 - 9:20am
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GSIP_kawashima4.pdf

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GSIP_kawashima4.pdf

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[1] Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa, "ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2285. Accessed: Nov. 21, 2017.
@article{2285-17,
url = {http://sigport.org/2285},
author = {Takashi Yoshida; Mitsuo Hayashi; Naoyuki Aikawa },
publisher = {IEEE SigPort},
title = {ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD},
year = {2017} }
TY - EJOUR
T1 - ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD
AU - Takashi Yoshida; Mitsuo Hayashi; Naoyuki Aikawa
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2285
ER -
Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa. (2017). ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD. IEEE SigPort. http://sigport.org/2285
Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa, 2017. ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD. Available at: http://sigport.org/2285.
Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa. (2017). "ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD." Web.
1. Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa. ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2285

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

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Authors:
Amine Chaabouni; Julien Lambert; Yann Gaudeau; Nicolas Tizon; Didier Nicholson; Jean-Marie Moureaux
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14 September 2017 - 7:54pm
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Poster Paper 2905 ICIP 2017

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[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: Nov. 21, 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

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Authors:
Rittwik Adhikari, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula
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13 September 2017 - 6:51am
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ICIP_17_Presentation_HK.pdf

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[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: Nov. 21, 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.

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Authors:
Abd-Krim Seghouane, Asif Iqbal
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11 September 2017 - 10:10pm
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Poster for ICIP 2017

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[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: Nov. 21, 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

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Authors:
Elmar Messner, Martin Hagmüller, Paul Swatek, Freyja-Maria Smolle-Jüttner, Franz Pernkopf
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20 March 2017 - 12:25pm
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[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: Nov. 21, 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

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Authors:
Lasith Adhikari, Roummel Marcia
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6 March 2017 - 10:40am
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[1] Lasith Adhikari, Roummel Marcia, "Non-Convex Sparse Optimization for Photon-Limited Imaging", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1650. Accessed: Nov. 21, 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.

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3 March 2017 - 6:30am
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FRIVortrag.pdf

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FRIVortrag.pdf

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[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: Nov. 21, 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

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