Title: Signal separation by symmetrical adaptive decorrelation - stability, convergence, and uniqueness
Authors: Van Gerven, Stefaan ×
Van Compernolle, Dirk #
Issue Date: Jul-1995
Publisher: Ieee-inst electrical electronics engineers inc
Series Title: IEEE Transactions on signal processing vol:43 issue:7 pages:1602-1612
Abstract: The performance of signal enhancement systems based on adaptive filtering is highly dependent on the quality of the noise reference, In the LMS algorithm, signal leakage into the mise reference leads to signal distortion and poor noise cancellation, The origin of the problem lies in the fact that LMS decorrelates the signal estimate with the noise reference, which, in the case of signal leakage, makes little sense, An algorithm is proposed that decorrelates the signal estimate with a ''signal-free'' noise estimate, obtained by adding a symmetric filter to the classical structure, The symmetric adaptive decorrelation (SAD) algorithm no longer makes a distinction between signal and noise and is therefore a signal separator rather than a noise canceler, Stability and convergence are of the utmost importance in adaptive algorithms and hence are carefully studied, Apart from limitations on the adaptation constants, stability around the desired solution can only be guaranteed for a subclass of signal mixtures, Furthermore, the decorrelation criterion does not yield a unique solution, and expressions for the ''phantom'' solutions are derived, Simulations with short FIR filters confirm the predicted behavior.
ISSN: 1053-587X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - PSI, Processing Speech and Images
× corresponding author
# (joint) last author

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