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Improvement of the Simplified Fast Transversal Filter Type Algorithm for Adaptive Filtering

By Madjid Arezki, Ahmed Benallal and Daoud Berkani

Abstract

<b>Problem statement:</b> In this study, we proposed a new algorithm M-SMFTF for adaptive filtering with fast convergence and low complexity. <b>Approach</b>: It was the result of a simplified FTF type algorithm, where the adaptation gain was obtained only from the forward prediction variables and using a new recursive method to compute the likelihood variable. <b>Results:</b> The computational complexity was reduced from 7L-6L, where L is the finite impulse response filter length. Furthermore, this computational complexity can be significantly reduced to (2L+4P) when used with a reduced P-size forward predictor. <b>Conclusion</b>: This algorithm presented a certain interest, for the adaptation of very long filters, like those used in the problems of echo acoustic cancellation, due to its reduced complexity, its numerical stability and its convergence in the presence of the speech signal

Topics: </keyword><keyword>Fast RLS, NLMS, FNTF, adaptive filtering, convergence speed, tracking capability, Electronic computers. Computer science, QA75.5-76.95, Instruments and machines, QA71-90, Mathematics, QA1-939, Science, Q, DOAJ:Computer Science, DOAJ:Technology and Engineering
Publisher: Science Publications
Year: 2009
DOI identifier: 10.3844/jcssp.2009.347.354
OAI identifier: oai:doaj.org/article:ef6d45e611404975a87e37352978127a
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