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...

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Bibliographic Details
Main Author: Paramanathan Lakshmikanthan.
Other Authors: Justin Dauwels
Format: Theses and Dissertations
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/53168
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Institution: Nanyang Technological University
Language: English
Description
Summary: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.