Multi-channel EEG compression based on matrix and tensor decompositions
Compression schemes for EEG signals are developed based on matrix and tensor decomposition. Various ways to arrange EEG signals into matrices and tensors are explored, and several matrix and tensor decomposition schemes are applied, including SVD, CUR, PARAFAC, the Tucker decomposition, and recent r...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
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2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/101285 http://hdl.handle.net/10220/18354 |
| _version_ | 1826114360714461184 |
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| author | Srinivasan, K. Dauwels, Justin Reddy, M. Ramasubba Cichocki, Andrzej |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Srinivasan, K. Dauwels, Justin Reddy, M. Ramasubba Cichocki, Andrzej |
| author_sort | Srinivasan, K. |
| collection | NTU |
| description | Compression schemes for EEG signals are developed based on matrix and tensor decomposition. Various ways to arrange EEG signals into matrices and tensors are explored, and several matrix and tensor decomposition schemes are applied, including SVD, CUR, PARAFAC, the Tucker decomposition, and recent random fiber selection approaches. Rate-distortion curves for the proposed matrix and tensor-based EEG compression schemes are computed. It shown that PARAFAC has the best compression performance in this context. |
| first_indexed | 2024-10-01T03:38:13Z |
| format | Conference Paper |
| id | ntu-10356/101285 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:38:13Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1012852020-03-07T13:24:50Z Multi-channel EEG compression based on matrix and tensor decompositions Srinivasan, K. Dauwels, Justin Reddy, M. Ramasubba Cichocki, Andrzej School of Electrical and Electronic Engineering IEEE International Conference on Acoustics, Speech and Signal Processing (2011 : Prague, Czech) DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Compression schemes for EEG signals are developed based on matrix and tensor decomposition. Various ways to arrange EEG signals into matrices and tensors are explored, and several matrix and tensor decomposition schemes are applied, including SVD, CUR, PARAFAC, the Tucker decomposition, and recent random fiber selection approaches. Rate-distortion curves for the proposed matrix and tensor-based EEG compression schemes are computed. It shown that PARAFAC has the best compression performance in this context. Accepted version 2013-12-20T03:14:33Z 2019-12-06T20:36:05Z 2013-12-20T03:14:33Z 2019-12-06T20:36:05Z 2011 2011 Conference Paper Dauwels, J., Srinivasan, K., Reddy, M. R., & Cichocki, A. (2011). Multi-channel EEG compression based on matrix and tensor decompositions. 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 629-632. https://hdl.handle.net/10356/101285 http://hdl.handle.net/10220/18354 10.1109/ICASSP.2011.5946482 156919 en © 2011 IEEE. This is the author created version of a work that has been peer reviewed and accepted for publication by 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [DOI:http://dx.doi.org/10.1109/ICASSP.2011.5946482]. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Srinivasan, K. Dauwels, Justin Reddy, M. Ramasubba Cichocki, Andrzej Multi-channel EEG compression based on matrix and tensor decompositions |
| title | Multi-channel EEG compression based on matrix and tensor decompositions |
| title_full | Multi-channel EEG compression based on matrix and tensor decompositions |
| title_fullStr | Multi-channel EEG compression based on matrix and tensor decompositions |
| title_full_unstemmed | Multi-channel EEG compression based on matrix and tensor decompositions |
| title_short | Multi-channel EEG compression based on matrix and tensor decompositions |
| title_sort | multi channel eeg compression based on matrix and tensor decompositions |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing |
| url | https://hdl.handle.net/10356/101285 http://hdl.handle.net/10220/18354 |
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