Compression of EEG using tensor decomposition

Modem applications of EEG require acquisition, storage and transmission of large amount of EEG data. Therefore efficient data compression is a must in order to avoid the complexities in handling the EEG data recorded from multiple channels. The Tensor de- compositions have been widely used in the an...

Full description

Saved in:

Bibliographic Details
Main Author:	Paramanathan Lakshmikanthan.
Other Authors:	Justin Dauwels
Format:	Theses and Dissertations
Language:	English
Published:	2013
Subjects:	DRNTU::Engineering::Electrical and electronic engineering
Online Access:	http://hdl.handle.net/10356/53168
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-53168
record_format	dspace
spelling	sg-ntu-dr.10356-531682023-07-04T16:04:02Z Compression of EEG using tensor decomposition Paramanathan Lakshmikanthan. Justin Dauwels School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Modem applications of EEG require acquisition, storage and transmission of large amount of EEG data. Therefore efficient data compression is a must in order to avoid the complexities in handling the EEG data recorded from multiple channels. The Tensor de- compositions have been widely used in the analysis of multidimensional data. During the last decade, the usage of tensors was extended to diverse applications including image and signal processing, feature extraction and pattern recognition of brain waves. The success- full application of tensor methods for Brain wave analysis and the natural representation of EEG provided by tensors suggested that it can be effectively used for EEG compression as well. Master of Science (Computer Control and Automation) 2013-05-30T04:49:15Z 2013-05-30T04:49:15Z 2011 2011 Thesis http://hdl.handle.net/10356/53168 en 64 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
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering Paramanathan Lakshmikanthan. Compression of EEG using tensor decomposition
description	Modem applications of EEG require acquisition, storage and transmission of large amount of EEG data. Therefore efficient data compression is a must in order to avoid the complexities in handling the EEG data recorded from multiple channels. The Tensor de- compositions have been widely used in the analysis of multidimensional data. During the last decade, the usage of tensors was extended to diverse applications including image and signal processing, feature extraction and pattern recognition of brain waves. The success- full application of tensor methods for Brain wave analysis and the natural representation of EEG provided by tensors suggested that it can be effectively used for EEG compression as well.
author2	Justin Dauwels
author_facet	Justin Dauwels Paramanathan Lakshmikanthan.
format	Theses and Dissertations
author	Paramanathan Lakshmikanthan.
author_sort	Paramanathan Lakshmikanthan.
title	Compression of EEG using tensor decomposition
title_short	Compression of EEG using tensor decomposition
title_full	Compression of EEG using tensor decomposition
title_fullStr	Compression of EEG using tensor decomposition
title_full_unstemmed	Compression of EEG using tensor decomposition
title_sort	compression of eeg using tensor decomposition
publishDate	2013
url	http://hdl.handle.net/10356/53168
_version_	1772827700728168448

Compression of EEG using tensor decomposition

Similar Items