Prototype filter design for subband adaptive filtering structures with critical sampling

Abstract

In adaptive filtering, new structures and algorithms are frequently proposed with the objective of increasing the convergence speed and/or reducing the computational complexity of the conventional algorithms, mainly for applications which require a large number of adaptive coefficients. In such applications, adaptive subband structures are specially attractive since the adaptation and filtering are performed at a reduced sampling rate. Recently, a new adaptive filtering structure with critical sampling was proposed, which is able to model exactly any finite impulse response system. In this paper we propose optimization procedures to select the filter bank coefficients for the improvement of the convergence behavior of adaptive subband algorithms.