Method Research on Effictive Seperated ICA Algorithm to Sub-Gaussian Distribution Audio Signal
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Graphical Abstract
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Abstract
An effictive seperated independent component analysis (ICA) algorithm is obtained by introducing a skewness-adjusting parameter to the Pearson mixture density model in extended Infomax algorithm. This model with skewness-adjusting parameter can cover a wider range of sub-Gaussian distribution including asymmetrical and multi-modal ones, resulting in more precisely approximating source's density. When dealing with non-skewed mixed sources, the new algorithm can achieve less steady-state error while maintaining fast convergence speed.
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