Adaptive filtering in subbands using a weighted criterion

Classical transform-domain algorithms adapt the filter coefficients (in each “frequency bin”) by minimizing a criterion depending on a full-band time-domain error. This paper proposes an algorithm which updates each portion of the frequency response of the adaptive filter according to the error in the same subband. For this purpose, a multirate adaptive filter is used where a subband decomposition of the error is performed using critically sampled lossless perfect reconstruction filter banks. This new algorithm is based on the minimization of a weighted criterion by a stochastic gradient algorithm and leads to improvements in the convergence rate compared to both LMS and classical frequency domain algorithms