17 July 1998 Simultaneous diagonalization algorithm for blind source separation based on subband filtered features
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Abstract
Blind source separation (BSS) has received increased attention in the signal processing literature. the goal of blind source separation is signal recovery from an unknown channel through the maximization (or minimization) of some independence criterion. In our previous work, we derived a generalized criterion (simultaneous diagonalization of correlation matrices -- SDOC) for blind source separation and explored the time-frequency structure of nonstationary signals like speech. In this paper we analyze first the identifiability of sources and apply subband filters for feature extraction to improve the BSS performance of the SDOC algorithm in the realistic but difficult situation when the background noise is not negligible.
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Hsiao-Chun Wu, Hsiao-Chun Wu, Jose C. Principe, Jose C. Principe, } "Simultaneous diagonalization algorithm for blind source separation based on subband filtered features", Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327121; https://doi.org/10.1117/12.327121
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