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A second-order statistics based dual-linear predictor structure is proposed for blind source extraction from noisy instantaneous mixtures. The noise component is assumed to be spatially and temporally white, but the variance information of noise is not required. A detailed proof of the proposed approach is provided and an adaptive algorithm is developed. Simulation results show that it can extract...
The canonical correlation analysis (CCA) approach is generalised to accommodate the case with added white noise. It is then applied to the blind source separation (BSS) problem for noisy mixtures. An adaptive blind source extraction algorithm is derived based on this idea. A proof is provided that by this generalised CCA approach, the source signals can be recovered successfully, which is also supported...
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