Classification of Electroencephalogram Using Artificial Neural Networks

Tsoi, A C; So, D S C; Sergejew, A

Classification of Electroencephalogram Using Artificial Neural Networks

NeurIPS 1993 pp. 1151-1158

/neurips/1993/tsoi1993neurips-classification/

Abstract

In this paper, we will consider the problem of classifying electroencephalo(cid:173) gram (EEG) signals of normal subjects, and subjects suffering from psychi(cid:173) atric disorder, e.g., obsessive compulsive disorder, schizophrenia, using a class of artificial neural networks, viz., multi-layer perceptron. It is shown that the multilayer perceptron is capable of classifying unseen test EEG signals to a high degree of accuracy.

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Text

Tsoi et al. "Classification of Electroencephalogram Using Artificial Neural Networks." Neural Information Processing Systems, 1993.

Markdown

[Tsoi et al. "Classification of Electroencephalogram Using Artificial Neural Networks." Neural Information Processing Systems, 1993.](https://mlanthology.org/neurips/1993/tsoi1993neurips-classification/)

BibTeX

@inproceedings{tsoi1993neurips-classification,
  title     = {{Classification of Electroencephalogram Using Artificial Neural Networks}},
  author    = {Tsoi, A C and So, D S C and Sergejew, A},
  booktitle = {Neural Information Processing Systems},
  year      = {1993},
  pages     = {1151-1158},
  url       = {https://mlanthology.org/neurips/1993/tsoi1993neurips-classification/}
}