Least squares support vector machine employing model-based methods coefficients for analysis of EEG signals

@article{beyli2010LeastSS,
  title={Least squares support vector machine employing model-based methods coefficients for analysis of EEG signals},
  author={Elif Derya {\"U}beyli},
  journal={Expert Syst. Appl.},
  year={2010},
  volume={37},
  pages={233-239}
}
The aim of the study is classification of the electroencephalogram (EEG) signals by combination of the model-based methods and the least squares support vector machines (LS-SVMs). The LS-SVMs were implemented for classification of two types of EEG signals (set A – EEG signals recorded from healthy volunteers with eyes open and set E – EEG signals recorded from epilepsy patients during epileptic seizures). In order to extract the features representing the EEG signals, the spectral analysis of… CONTINUE READING

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