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In this paper two methods for blind source separation of nonstationary signals, such as electroencephalogram output, applied to time frequency distributions are compared through implementation in a virtual instrument. Both methods are based on image processing approaches, but adopt different strategies for solving the blind source separation problem: the first method is based on a data clustering...
Separation of different signal components, produced by one or more sources, is a problem encountered in many signal processing applications. This paper proposes a fully automatic undetermined blind source separation method, based on a peak detection and extraction technique from a signal time-frequency distribution (TFD). Information on the local number of components is obtained from the TFD Short-term...
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