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- W2183587580 abstract "Blind source separation (BSS) aims to find unknown sources from a number of known mixtures. Under-determined blind source separation aims to separate N non-stationary sources from M (M<N) mixtures. Proposed system presents a time-frequency approach (TF) to under-determined blind source separation of N non-stationary sources from M mixtures(M<N).Method involves a linear mixing model followed by Wigner-Ville distribution and algorithm based on Khatri-Rao product. Improved approach include a two step approach which involves the estimation of the mixing matrix where negative values of auto WVD of the sources are fully considered and secondly auto-term TF points are extracted. After extracting the auto-term TF points source WVD values at every TF point are computed using a new algorithm based on Khatri-Rao product. Thus sources are separated with the proposed approach no matter how many active sources are present as long as N � 2M-1.For better performance linear mixing model is replaced with laplacian mixing model followed by Wigner-ville distribution and Khatri-rao product. Simulation results are presented to show the performance efficiency with different mixing models and clustering techniques used along with it." @default.
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- W2183587580 date "2013-01-01" @default.
- W2183587580 modified "2023-09-27" @default.
- W2183587580 title "Under-determined Blind Source Separation of Audio Signals using Laplacian Mixing Model" @default.
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