Non-uniform subband adaptive filtering with critical sampling

Adaptive subband structures have been proposed with the objective of increasing the convergence speed and/or reducing the computational complexity of conventional adaptive algorithms, mainly for applications which require a large numb of adaptive coefficients. In this paper, we present a nonuniform subband structure with critical sampling, which is able of exact modeling an arbitrary FIR system. We also derive an LMS-type adaptation algorithm with normalized step-sizes, which works the lowest downsampling rate and minimizes the average of the subband squared-errors. A convergence analysis of the propos adaptation algorithm is presented, from which its convergence rate can be estimated