Abstract
Fast independent component analysis (FastICA) algorithm separates the independent sources from their mixtures by measuring non-Gaussian. However, it may lead to the slowing down of convergence speed in the algorithm with improper step, even non-convergence, To overcome these shortcomings and meet the needs of the separation of mixed sound signals, improved FastICA algorithm is used in this paper, which converges much faster and does not need to select the step size parameters manually. Moreover, a detailed description of blind source separation on DSP platform is concluded. Finally, the improved algorithm is applied to the voice signal separation, whose experimental results demonstrate the effectiveness of the presented hardware FastICA as expected.
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