Research Article
Dynamic Principal Component Analysis with Nonoverlapping Moving Window and Its Applications to Epileptic EEG Classification
Table 1
The average classification accuracy (i.e., the proportion of all signal types correctly detected) using methods of FFPC and PCPEM with different values of for the epileptic seizure detection and diagnosis problems using the EEGs dataset from the University of Bonn.
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