Evaluating the Performance of Three Feature Sets for Brain-Computer Interfaces with an Early Stopping MLP Committee

@inproceedings{Varsta2000EvaluatingTP,
  title={Evaluating the Performance of Three Feature Sets for Brain-Computer Interfaces with an Early Stopping MLP Committee},
  author={Markus Varsta and Jukka Heikkonen and Jos{\'e} del R. Mill{\'a}n and Josep Mouri{\~n}o},
  booktitle={ICPR},
  year={2000}
}
We present preliminary classification results for a real time brain-computer interface. Our approach seeks to build individual brain intel-faces rather than universal ones. This means that the intel-face should adapt to its owner, as it will incorporate a neural classifier that learns user-specific features. Three feature sets extracted with Fourier transform, autoregressive models and wavelets were evaluated with early stopping MLP committee. The goal was to class i b EEG patterns related to… CONTINUE READING
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Forest change detection via landsat tm difference features

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