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Separation of the EEG signal using improved fastica based on kurtosis
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ahmad, Tahir |
| Copyright Year | 2011 |
| Abstract | Independent component analysis (ICA) is a computational method to solve blind source separation (BSS) problem. In this paper, an improved FastICA based on Kurtosis was proposed to separate EEG signal. It was adopted from the gradient descent algorithm to improve the converge rate. Improved FastICA method was applied to separate EEG signal from a patient who had epilepsy seizure. The separation results proved that the method was feasible and effective. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ajbasweb.com/old/ajbas/2011/September-2011/2152-2156.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |