How to Reduce Classification Error in ERP-Based BCI: Maximum Relative Areas as a Feature for P300 Detection

Vinicio Changoluisa, Pablo Varona, Francisco B. Rodríguez. How to Reduce Classification Error in ERP-Based BCI: Maximum Relative Areas as a Feature for P300 Detection. In Ignacio Rojas, Gonzalo Joya, Andreu Català, editors, Advances in Computational Intelligence - 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, Cadiz, Spain, June 14-16, 2017, Proceedings, Part II. Volume 10306 of Lecture Notes in Computer Science, pages 486-497, Springer, 2017. [doi]

@inproceedings{ChangoluisaVR17,
  title = {How to Reduce Classification Error in ERP-Based BCI: Maximum Relative Areas as a Feature for P300 Detection},
  author = {Vinicio Changoluisa and Pablo Varona and Francisco B. Rodríguez},
  year = {2017},
  doi = {10.1007/978-3-319-59147-6_42},
  url = {https://doi.org/10.1007/978-3-319-59147-6_42},
  researchr = {https://researchr.org/publication/ChangoluisaVR17},
  cites = {0},
  citedby = {0},
  pages = {486-497},
  booktitle = {Advances in Computational Intelligence - 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, Cadiz, Spain, June 14-16, 2017, Proceedings, Part II},
  editor = {Ignacio Rojas and Gonzalo Joya and Andreu Català},
  volume = {10306},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-59147-6},
}