Using a Chain of LVQ Neural Networks for Pattern Recognition of EEG Signals Related to Intermittent Photic-Stimulation

This work reports the use of neural networks for pattern recognition in electroencephalographic signals related to intermittent photic-stimulation. Due to the low signal/noise ratio of this kind of signal, it was necessary the use of a spectrogram as a predictor and a chain of LVQ neural networks. The efficiency of this pattern recognition structure was tested for many different configurations of the neural networks parameters and different volunteers. A direct relationship between the dimension of the neural networks and their performance was observed. Results so far encourage new experiments and demonstrate the feasibility of the proposed system for real-time pattern recognition of complex signals.

• Type: Conference
• Year: 2002
• Where: SBRN
• Authors: Mauricio Kugler, Heitor Silvério Lopes
• Keywords: Artificial Intelligence, LVQ Neural Networks, Neural Networks, Pattern Recognition, SBRN 2002