I. Introduction
Signal processing algorithms, especially within speech and audio, rely frequently on filterbanks which provide a time-frequency representation of the signal [1]. Such representations are attractive for three main reasons. Firstly, they give access to components of the signal which carry a physically interpretation, enabling easy application of physically motivated methods. Secondly, since many methods, such as the short-time Fourier transform, give frequency components which are approximately uncorrelated, we can process frequency components independently from each other. This allows design of efficient processing algorithms since we do not have to take cross-correlations into account. Thirdly, to compute time-frequency transforms, we can use superfast algorithms such as the fast Fourier transform (FFT).