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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chavan, A. Kolte, M. |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Electron. & Tele-Commun., Maharashtra Inst. of Technol., Pune, India (Kolte, M.) || Dept. of Biomed. Eng., Vidyalankar Inst. of Technol., Mumbai, India (Chavan, A.) |
| Abstract | In this paper, wavelet based multi scale PCA algorithm is proposed and demonstrated to enhance the classification performance in identifying EEG signals. The signal decomposition is done using wavelet transform, followed by the de-correlation using PCA, to achieve maximum compression, while simultaneously preserving the dominant modes of the signal and bad data rejection. The optimum decomposition scale of wavelet transform is selected based on the energy of wavelet coefficients in each scale. The proposed algorithm employing multi scale PCA computes the principal components of the wavelet coefficients at each scale, followed by combining the results at relevant scales. The wavelet coefficients of a particular scale corresponding to the dominant eigen values are retained for signal compression. These results in effectively compresses the EEG signals while preserving the model information of the signal. |
| Starting Page | 1056 |
| Ending Page | 1059 |
| File Size | 1513891 |
| Page Count | 4 |
| File Format | |
| e-ISBN | 9781479971657 |
| DOI | 10.1109/IIC.2015.7150902 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-28 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transform EEG Discrete wavelet transforms Multi-scale Approximation methods Signal resolution Multiresolution analysis PCA |
| Content Type | Text |
| Resource Type | Article |
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