BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS

The brain source localization information is used to diagnose various brain disorders such as epilepsy, schizophrenia, stress, depression and Alzheimer. It is an ill-posed problem in nature affected by uncertainty in solution. Different algorithms are proposed for the solution of this ill-posed p...

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Main Author: MUNSIF , ALI JATOI
Format: Thesis
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.21897 /
Published: 2016
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access: http://utpedia.utp.edu.my/21897/1/2016%20-%20ELECTRICAL%20%26%20ELECTRONIC%20-%20BRAIN%20SOURCE%20LOCALIZATION%20TECHNIQUE%20FOR%20EEG%20SIGNALS%20BASED%20ON%20ENHANCED%20MULTIPLE%20SPARSE%20PRIORS%20-%20MUNSIF%20ALI%20JATOI.pdf
http://utpedia.utp.edu.my/21897/
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spelling utp-utpedia.218972021-09-25T20:45:24Z http://utpedia.utp.edu.my/21897/ BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS MUNSIF , ALI JATOI TK Electrical engineering. Electronics Nuclear engineering The brain source localization information is used to diagnose various brain disorders such as epilepsy, schizophrenia, stress, depression and Alzheimer. It is an ill-posed problem in nature affected by uncertainty in solution. Different algorithms are proposed for the solution of this ill-posed problem which include minimum norm estimation (MNE), second order Laplacian based low resolution brain electromagnetic tomography (LORETA), standardized LORETA (sLORETA), exact LORETA, subspace based multiple signal classifier (MUSIC), Beamformer and Bayesian framework based multiple source priors (MSP). The solution provided by each of the algorithms mentioned above is characterized by various parameters which include the accuracy, computational complexity and localization error. The existing algorithms suffer from low resolution (LORETA family), high computational time (subspace algorithms and FOCUSS, WMN-LORETA) and no validation. 2016-11 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/21897/1/2016%20-%20ELECTRICAL%20%26%20ELECTRONIC%20-%20BRAIN%20SOURCE%20LOCALIZATION%20TECHNIQUE%20FOR%20EEG%20SIGNALS%20BASED%20ON%20ENHANCED%20MULTIPLE%20SPARSE%20PRIORS%20-%20MUNSIF%20ALI%20JATOI.pdf MUNSIF , ALI JATOI (2016) BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS. PhD thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
MUNSIF , ALI JATOI
BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS
description The brain source localization information is used to diagnose various brain disorders such as epilepsy, schizophrenia, stress, depression and Alzheimer. It is an ill-posed problem in nature affected by uncertainty in solution. Different algorithms are proposed for the solution of this ill-posed problem which include minimum norm estimation (MNE), second order Laplacian based low resolution brain electromagnetic tomography (LORETA), standardized LORETA (sLORETA), exact LORETA, subspace based multiple signal classifier (MUSIC), Beamformer and Bayesian framework based multiple source priors (MSP). The solution provided by each of the algorithms mentioned above is characterized by various parameters which include the accuracy, computational complexity and localization error. The existing algorithms suffer from low resolution (LORETA family), high computational time (subspace algorithms and FOCUSS, WMN-LORETA) and no validation.
format Thesis
author MUNSIF , ALI JATOI
author_sort MUNSIF , ALI JATOI
title BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS
title_short BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS
title_full BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS
title_fullStr BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS
title_full_unstemmed BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS
title_sort brain source localization technique for eeg signals based on enhanced multiple sparse priors
publishDate 2016
url http://utpedia.utp.edu.my/21897/1/2016%20-%20ELECTRICAL%20%26%20ELECTRONIC%20-%20BRAIN%20SOURCE%20LOCALIZATION%20TECHNIQUE%20FOR%20EEG%20SIGNALS%20BASED%20ON%20ENHANCED%20MULTIPLE%20SPARSE%20PRIORS%20-%20MUNSIF%20ALI%20JATOI.pdf
http://utpedia.utp.edu.my/21897/
_version_ 1741195800961089536
score 11.62408

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