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Multi-channel EEG signal segmentation and feature extraction
2010
2010 IEEE 14th International Conference on Intelligent Engineering Systems
Signal analysis of multi-channel data form a specific area of general digital signal processing methods. The paper is devoted to application of these methods for electroencephalogram (EEG) signal processing including signal de-noising, evaluation of its principal components and segmentation based upon feature detection both by the discrete wavelet transform (DWT) and discrete Fourier transform (DFT). The self-organizing neural networks are then used for pattern vectors classification using a
doi:10.1109/ines.2010.5483824
fatcat:o5huqvbea5cergzheffjeip524