Estimation of the Number of Unknown Source Signals and Its Application to EEG Analysis
Takaaki Ishibashi, Masataka Sugahara, Shingo Tamatsuka, Katsuhiro Inoue, Hiromu Gotanda, Kousuke Kumamaru · Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications · 2007
This paper proposes a feature extraction method based on ICA (Independent Component Analysis) for EEG (electroencephalogram) signals under visual recognition obtained by oddball task experiments. The proposed method estimates the number of characteristic signals. Some characteristic peaks appear in the separated signals by ICA using this estimated number.