Automatic classification of EEG segments and extraction of representative ones by dynamic clusters method.

@article{Krajca1984AutomaticCO,
  title={Automatic classification of EEG segments and extraction of representative ones by dynamic clusters method.},
  author={Vladimir Krajca},
  journal={Activitas nervosa superior},
  year={1984},
  volume={26 2},
  pages={118-28}
}
Use of the dynamic clusters method for automatic extraction of compressed information about recorded EEG signal is presented. The computer first divides the record into quasi-stationary segments by means of adaptive segmentation. Second, the extracted segments are classified by a method of dynamic clusters into homogeneous classes. One part of the used clustering algorithm permits to specify and draw the most typical class members, which may represent the whole studied EEG signal and may be… CONTINUE READING