In recent years,much research has been focused on separating acoustic sources from their mixtures.Degenerate Unmixing Estimation Technique(DUET)is one of the widely popular meth-ods of Blind Source Separation(BSS)in u...In recent years,much research has been focused on separating acoustic sources from their mixtures.Degenerate Unmixing Estimation Technique(DUET)is one of the widely popular meth-ods of Blind Source Separation(BSS)in underdetermined scenarios.DUET is based on a signal recovery sparsity algorithm whose performance is strongly influenced by sparsity in the Time-Frequency(TF)domain.Noises and an several sources in mixtures limit the sparsity resulting in performance degradation in DUET.Here an enhanced strategy has been adopted by combin-ing DUET with adaptive noise cancellation utilising the Dual-Tree Complex Wavelet Transform(DTCWT)as a pre-processor and TF refinement utilising Synchroextracting Transform(SET)as a post-processor.This improves the sparsity of sources and energy concentrations in a TF rep-resentation.Results of the signal separation performance evaluation reveal that the proposed algorithm outperforms conventional DUET in signal separation,especially in real-time scenarios.展开更多
文摘In recent years,much research has been focused on separating acoustic sources from their mixtures.Degenerate Unmixing Estimation Technique(DUET)is one of the widely popular meth-ods of Blind Source Separation(BSS)in underdetermined scenarios.DUET is based on a signal recovery sparsity algorithm whose performance is strongly influenced by sparsity in the Time-Frequency(TF)domain.Noises and an several sources in mixtures limit the sparsity resulting in performance degradation in DUET.Here an enhanced strategy has been adopted by combin-ing DUET with adaptive noise cancellation utilising the Dual-Tree Complex Wavelet Transform(DTCWT)as a pre-processor and TF refinement utilising Synchroextracting Transform(SET)as a post-processor.This improves the sparsity of sources and energy concentrations in a TF rep-resentation.Results of the signal separation performance evaluation reveal that the proposed algorithm outperforms conventional DUET in signal separation,especially in real-time scenarios.
