Kurtosis-based Projection Pursuit for Signal Separation of Traditional Musical Instruments
نویسندگان
چکیده
Signal separation is a substantial problem in digital signal processing. The objective of signal separation from a musical composition is to decompose the composition into signals of individual musical instruments. One method that can be used is Projection Pursuit (PP) that similar with Independent Component Analysis (ICA). PP can determine source signals by projecting the data to find the most nonGaussian distribution. In this paper we propose a method based on kurtosis as a criteria to determine nonGaussianity. We use Mean Square Error (MSE) and Signal-to-Noise Ratio (SNR) to evaluate the accuracy of signal separation. We conducted an experiment on a synthetic and real signal mixture of traditional musical instruments i.e. Javanese Gamelan. The result showed that the minimum value of MSE for separation signal using Kurtosis-based PP (K-PP) is 1.02 × 10 -5 lower than FastICA and PP. Meanwhile, the maximum value of SNR with the proposed method is 42.13 dB higher than the others.
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