Echo Cancellation using PMSAF and Compare the performance with NLMS and improved PNLMS under different Impulse responses

Abstract: In the field of signal processing adaptive filtering is a major subject which has vast applications in speech processing e.g. speech coding, speech enhancement, echo cancellation and interference. Echo is the major problem in the communication systems. There are two major types of echoes hybrid and acoustic echoes. In order to remove these echoes the most important method for removing these echoes is through cancellation. Adaptive filters are used to estimate the replication of echoes and then subtracted from the infected signal. . We introduced subband filters to improve the performance of adaptive filter (time domain). Due to small adaptive filters in the subband filter banks, we can improve the reduction of complexity, computational and convergence level as compared with others. The major goal of this thesis is to present the echo cancellation using the multiband subband adaptive filtering and also compare the performance with NLMS and Improved PNLMS using different impulse responses. PMSAF algorithm behaves continuously better convergense rate with excitation signal (colored noise and speech signal) for both impulse responses (sparse and dispersive) as compared with IPNLMS and NLMS algorithms.