New Fixed-point Ica Algorithms for Convolved Mixtures
نویسندگان
چکیده
One of the most powerful techniques applied to blind audio source separation is Independent Component Analysis (ICA). For the separation of audio sources recorded in a real environment, we need to model the mixing process as convolutional. Many methods have been introduced for separating convolved mixtures, the most successful of which require working in the frequency domain [1], [2], [3], [4]. Most of these methods perform efficient separation of convolved mixtures, however they are relatively slow. The authors propose two fixed-point algorithms for performing fast frequency domain ICA.
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