QRD-based unconstrained optimal filtering for acoustic noise reduction

We describe a new adaptive filtering algorithm based upon QR-decomposition for optimal multichannel filtering with an “unknown” desired signal, as well as its application to multi-channel acoustic noise reduction. A recursively calculated adaptive filter then optimally estimates the speech component in a noisy signal. The complexity of this algorithm is about 7 times lower than that of existing related algorithms, which are mainly based upon GSVD-decompositions, while performance is kept at the same level. Finally, it is shown how a parameter can be introduced which can be tuned to tradeoff noise reduction for signal distortion. [Copyright &y& Elsevier]