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A Robust ICA-Based Adaptive Filter Algorithm for System Identification
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DOI：10.1109/TCSII.2008.2008060.png)
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Abstract
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This paper proposes a new adaptive filter algorithm for system identification using independent component analysis. The additive noise is considered as an independent component to be separated from the noisy observation and is simultaneously estimated online. The proposed algorithm is derived by minimizing the mutual information between the estimated additive noise and the input signal. The local convergence conditions are also derived. The proposed algorithm can be directly applied to the acoustic echo canceller without any double-talk detector. Some simulations have been carried out to illustrate its effectiveness for synthetic and real speech signals.
Keywords:
Adaptive filters
robustness
signal processing
system identification
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