Abstract
A comparison of adaptive IIR (infinite impulse response) filters with gradient-based adaptation algorithms is presented. The following algorithms were investigated: series parallel LMS (SP-LMS), equation error formulation LMS (EEF-LMS), bias-remedy LMS (BRLMS) alternate filtering mode (AFM), simple hyperstable adaptive recursive filter (SHARF), and normalized LMS (NLMS), which served as an FIR comparison case. The classification structure employed clearly illustrates the relationships of the algorithms to each other; additionally, other feasible filter methodologies for further investigation were revealed. All algorithms were implemented on a Motorola 56001. Correct normalization of the adaptation stepsize played a critical role in the results, which were obtained by real-time measurements. Only the SHARFS and BRLMS algorithms fulfil the requirements of a low-cost hybrid echo canceller.

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