IMPROVING ROBUSTNESS OF BLIND ADAPTIVE MULTICHANNEL IDENTIFICATION ALGORITHMS USING CONSTRAINTS (ThuAmPO2)

Author(s) : Md. Kamrul Hasan (Imperial College London, United Kingdom) Jacob Benesty (INRS-EMT, University of Quebec, Canada) Patrick A. Naylor (Imperial College London, United Kingdom) Darren B. Ward (Imperial College London, United Kingdom)

Abstract : This paper shows that the robustness of the normalized multichannel frequency-domain LMS algorithm reported in [1] can be improved using constraints in the adaptation rule. In the identification of acoustic impulse responses with leading bulk zeros from noisy observations the proposed constraint shows significant performance improvement in terms of normalized projection misalignment. Experimental results for various simulated conditions are presented to justify our claim.

Menu