A Family of Set-membership Affine Projection Adaptive Filter Algorithms
نویسندگان
چکیده
In this paper, we extend the set-membership (SM) adaptive filtering approach to the various affine projection (AP) adaptive filter algorithms to propose the computationally efficient algorithms. Based on this, the SM-APA, SM selective regressor APA (SM-SR-APA), SM dynamic selection APA (SM-DS-APA) and SM selective partial update APA (SM-SPU-APA) are established. The SM-SR-APA reduces complexity by selecting a subset of input regressors at every iteration. In SM-DS-APA, the dynamic selection of input vectors is used during the adaptation. The filter coefficients are partially updated in SM-SPU-APA. Also by combination of SM and SPU approaches, the SM-SPU-SR-APA and SM-SPU-DS-APA are introduced. We demonstrate the good performance of the presented algorithms for system identification, line and acoustic echo cancellation applications.
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