Improved Blind Separations of Nonstationary Sources Based on Spatial Time-frequency Distributions
نویسندگان
چکیده
Blind source separation (BSS) based on spatial time-frequency distributions (STFDs) provides improved performance over blind source separation methods based on second-order statistics, when dealing with signals that are localizable in the time-frequency (t-f) domain. In this paper, we introduce a simple method for autoterm and crossterm selection, and propose the use of STFD matrices for both prewhitening and mixing matrix recovery. T-f grouping is also proposed for improved blind separation of nonstationary signals. This method provides robust performance to noise and allows reduction of the number of sources considered for separation.
منابع مشابه
Blind Separations of Nonstationary Sources Based on Spatial Time-Frequency Distributions
Blind source separation (BSS) based on spatial time-frequency distributions (STFDs) provides improved performance over blind source separation methods based on second-order statistics, when dealing with signals that are localizable in the time-frequency (t-f) domain. In this paper, we propose the use of STFD matrices for both whitening and mixing matrix recovery, two stages commonly required in...
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Blind source separation (BSS) based on spatial time-frequency distributions (STFDs) provides improved performance over blind source separation methods based on second-order statistics, when dealing with signals that are localized in the time-frequency (t-f) domain. In this paper, we propose the use of STFD matrices for both whitening and recovery of the mixing matrix, which are two stages commo...
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