Adaptive Filters Employing Partial Updates
نویسنده
چکیده
{ In some adaptive ltering applications, the least-mean-square (LMS) algorithm may be too computationally-and memory-intensive to implement. In this paper , we analyze two adaptive algorithms that update only a portion of the coeecients of the adaptive lter per iteration. These algorithms use decimated versions of the error and regressor signals, respectively. Simulations verify the accuracy of the analyses, and the robustness of the algorithms is also explored.
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