Filter bank design for a subband adaptive filtering structure with critical sampling

Subband adaptive filtering structures are attractive in applications such as acoustic echo cancellation and channel equalization, due to their properties of decorrelating the input signal and reducing the computational complexity. Recently, a new adaptive filtering structure with critical sampling was proposed. In this paper, we describe an optimization procedure to select the analysis and synthesis filter banks of this new subband structure, so that minimum steady-state mean square error or fastest convergence rate can be achieved. Such filter-bank design method is based on a theoretical analysis of the convergence properties of the adaptation algorithm and uses a nonlinear optimization routine. Computer simulations illustrate the convergence improvements that can be obtained with the filter banks designed by the proposed method.