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In this paper, we proposed the approach which combines inverse filter criteria with non-Gaussianity to separate convolutive mixtures of speech in the time domain. In this case, the proposed method first extract innovation processes of speech sources by non-Gaussianity maximization and then artificially color them by re-coloration filters. Computer simulation experiments are presented to illustrate...
The paper presents a simple and efficient algorithm that separates three speech signals from two mixtures. Cochlear filtering and the ratio between the time-frequency representations of the two mixtures are used. It follows a method that works for both convolutive and instantaneous mixing models. Simulation results are also presented to confirm the proposed approach.
In this paper, we propose a new blind multichannel adaptive filtering scheme, which incorporates a partial-updating mechanism in the error gradient of the update equation. The proposed blind processing algorithm operates in the time-domain by updating only a selected portion of the adaptive filters. The algorithm steers all computational resources to filter taps having the largest magnitude gradient...
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