Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface

This research thesis explores an efficient communication approach in P300 based single trial brain-computer interface (BCI). As a tool of rehabilitation engineering for the locked-in patients, the BCI is expected to be swift in performance and intelligent in recognition. With this aim, the objective...

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Main Author: Samraj, Andrews
Format: Thesis
Published: 2009
Subjects:
Online Access:http://shdl.mmu.edu.my/1781/
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author Samraj, Andrews
author_facet Samraj, Andrews
author_sort Samraj, Andrews
building MMU Institutional Repository
collection Online Access
description This research thesis explores an efficient communication approach in P300 based single trial brain-computer interface (BCI). As a tool of rehabilitation engineering for the locked-in patients, the BCI is expected to be swift in performance and intelligent in recognition. With this aim, the objectives of this thesis are to reduce noise from raw EEG signals using novel variants of principal component analysis (PCA) and singular value decomposition (SVD), to improve classification performance using Fuzzy ARTMAP, Simplified Fuzzy ARTMAP and a combination of other linear classifier and to reduce feature dimension and hardware requirement using genetic algorithm (GA).
first_indexed 2025-11-14T18:03:49Z
format Thesis
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institution Multimedia University
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last_indexed 2025-11-14T18:03:49Z
publishDate 2009
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spelling mmu-17812010-12-24T08:46:26Z http://shdl.mmu.edu.my/1781/ Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface Samraj, Andrews TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television P Philology. Linguistics This research thesis explores an efficient communication approach in P300 based single trial brain-computer interface (BCI). As a tool of rehabilitation engineering for the locked-in patients, the BCI is expected to be swift in performance and intelligent in recognition. With this aim, the objectives of this thesis are to reduce noise from raw EEG signals using novel variants of principal component analysis (PCA) and singular value decomposition (SVD), to improve classification performance using Fuzzy ARTMAP, Simplified Fuzzy ARTMAP and a combination of other linear classifier and to reduce feature dimension and hardware requirement using genetic algorithm (GA). 2009-01 Thesis NonPeerReviewed Samraj, Andrews (2009) Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface. PhD thesis, Multimedia University. http://vlib.mmu.edu.my/diglib/login/dlusr/login.php
spellingShingle TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
P Philology. Linguistics
Samraj, Andrews
Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface
title Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface
title_full Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface
title_fullStr Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface
title_full_unstemmed Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface
title_short Signal Processing and Classification of Visual Evoked Potentials in a Brain Computer Interface
title_sort signal processing and classification of visual evoked potentials in a brain computer interface
topic TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
P Philology. Linguistics
url http://shdl.mmu.edu.my/1781/
http://shdl.mmu.edu.my/1781/