Emotional state classification of brain signals using extreme learning machine (ELM) algorithm

Electroencephalogram (EEG) signals have been proven to have strong correlation with underlying human emotions. Numerous approaches have been reported for emotion recognition from EEG signals; however, not much effort has been performed in applying Wavelet Transform for emotion recognition from EEG s...

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Bibliographic Details
Main Author:	Yohanes, Rendi Ein Janvier.
Other Authors:	Huang Guangbin
Format:	Final Year Project
Language:	English
Published:	2012
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Online Access:	http://hdl.handle.net/10356/50056
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-50056
record_format	dspace
spelling	sg-ntu-dr.10356-500562023-07-07T16:56:09Z Emotional state classification of brain signals using extreme learning machine (ELM) algorithm Yohanes, Rendi Ein Janvier. Huang Guangbin Ser Wee School of Electrical and Electronic Engineering Centre for Signal Processing DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Electroencephalogram (EEG) signals have been proven to have strong correlation with underlying human emotions. Numerous approaches have been reported for emotion recognition from EEG signals; however, not much effort has been performed in applying Wavelet Transform for emotion recognition from EEG signals despite its proven effectiveness on non-stationary signal analysis. Bachelor of Engineering 2012-05-29T06:23:24Z 2012-05-29T06:23:24Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/50056 en Nanyang Technological University 73 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Yohanes, Rendi Ein Janvier. Emotional state classification of brain signals using extreme learning machine (ELM) algorithm
description	Electroencephalogram (EEG) signals have been proven to have strong correlation with underlying human emotions. Numerous approaches have been reported for emotion recognition from EEG signals; however, not much effort has been performed in applying Wavelet Transform for emotion recognition from EEG signals despite its proven effectiveness on non-stationary signal analysis.
author2	Huang Guangbin
author_facet	Huang Guangbin Yohanes, Rendi Ein Janvier.
format	Final Year Project
author	Yohanes, Rendi Ein Janvier.
author_sort	Yohanes, Rendi Ein Janvier.
title	Emotional state classification of brain signals using extreme learning machine (ELM) algorithm
title_short	Emotional state classification of brain signals using extreme learning machine (ELM) algorithm
title_full	Emotional state classification of brain signals using extreme learning machine (ELM) algorithm
title_fullStr	Emotional state classification of brain signals using extreme learning machine (ELM) algorithm
title_full_unstemmed	Emotional state classification of brain signals using extreme learning machine (ELM) algorithm
title_sort	emotional state classification of brain signals using extreme learning machine (elm) algorithm
publishDate	2012
url	http://hdl.handle.net/10356/50056
_version_	1772825269019607040

Emotional state classification of brain signals using extreme learning machine (ELM) algorithm

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