Partial update subband implementation of complex pseudo-affine projection algorithm on oversampled filterbanks

Fast adaptive algorithms targeted for low-resource implementation on oversampled filterbanks are discussed. First, simplifications to the Pseudo Affine Projection (PAP) are proposed that decrease the computation cost without degrading the performance. Next, the sequential update PAP algorithm is proposed to further decrease the computational complexity. It is shown that, unlike the partial update fast affine projection, increasing the decimation rate of the partial update algorithm does not lead to more aliasing in the sequential update PAP. Moreover. it is experimentally observed that with proper regularization or step-size scaling, the convergence rate of the sequential PAP is identical for various decimation factors of the partial update. The proposed methods are implemented and evaluated on a low-resource oversampled filterbank platform.