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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ping Guo Jing Wang Gao, X.Z. Tanskanen, J.M.A. |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Biomedical Engineering, Tampere University of Technology, Finland (Tanskanen, J.M.A.) || Laboratory of Image Processing and Pattern Recognition, Beijing Normal University, 100875, China (Ping Guo; Jing Wang) || Department of Automation and Systems Technology, Aalto University School of Electrical Engineering, Finland (Gao, X.Z.) |
| Abstract | In Epilepsy EEG signal classification, the main time-frequency features can be extracted by using sparse representation with marching pursuit (MP) algorithm. However, the computational burden is so heavy that it is almost impossible to apply MP to real time signal processing. To reduce complexity of sparse representation, we propose to adopt harmony search method in searching the best atoms. Because harmony search method can find the best atoms in continuous time-frequency dictionary, the performance of epilepsy EEG signal classification is enhanced. The validity of this method is proved by experimental results. |
| Starting Page | 283 |
| Ending Page | 288 |
| File Size | 288065 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467317139 |
| e-ISBN | 9781467317146 |
| e-ISBN | 9781467317122 |
| DOI | 10.1109/ICSMC.2012.6377715 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-10-14 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Electroencephalography Dictionaries Classification algorithms Training Matching pursuit algorithms Accuracy Sparse representation Harmony search method Electroencephalogram Seizure detection Overcomplete dictionary |
| Content Type | Text |
| Resource Type | Article |
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