Performance of Adaptive Filtering Algorithms: A Comparative Study
نویسندگان
چکیده
This paper presents a comparative performance study between the recently proposed time-varying LMS (TVLMS) algorithm and other two main adaptive approaches: the least-mean square (LMS) algorithm and the recursive leastsquares (RLS) algorithm. Three performance criteria are utilized in this study: the algorithm execution time, the minimum meansquared error (MSE), and the required filter order. The study showed that the selection of the filter order is based on a trade-off between the MSE performance and algorithm executive time. Results also showed that the execution time of the RLS algorithm increases more rapidly with the filter order than other algorithms.
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