Filter Bank Design for Subband Adaptive Filtering

Abstract: Adaptive filtering is an important subject in the field of signal processing and has numerous applications in fields such as speech processing and communications. Examples in speech processing include speech enhancement, echo- and interference- cancellation, and speech coding. Subband filter banks have been introduced in the area of adaptive filtering in order to improve the performance of time domain adaptive filters. The main improvements are faster convergence speed and the reduction of computational complexity due to shorter adaptive filters in the filter bank subbands. Subband filter banks, however, often introduce signal degradations. Some of these degradations are inherent in the structure and some are inflicted by filter bank parameters, such as analysis and synthesis filter coefficients. Filter banks need to be designed so that the application performance degradation is minimized. The presented design methods in this thesis aim to address two major filter bank properties, transmission delay in the subband decomposition and reconstruction as well as the total processing delay of the whole system, and distortion caused by decimation and interpolation operations. These distortions appear in the subband signals and in the reconstructed output signal. The thesis deals with different methods for filter bank design, evaluated on speech signal processing applications with filtering in subbands. Design methods are developed for uniform modulated filter banks used in adaptive filtering applications. The proposed methods are compared with conventional methods. The performances of different filter bank designs in different speech processing applications are compared. These applications are acoustic echo cancellation, speech enhancement including spectral estimation, subband beamforming, and subband system identification. Real speech signals are used in the simulations and results show that filter bank design is of major importance.