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To reduce the computational complexity of the adaptive filtering algorithm, a new affine projection algorithm based on set membership with partial-update(PU-SM-AP) is proposed. The new algorithm allows the reduction of the frequency of updates of the filter coefficients, where the filter coefficients are updated such that the output estimation error is upper bounded by a pre-determined threshold....
In this paper, an improved proportionate normalized least mean square (MPNLMS) algorithm incorporating a data selection strategy based on the set-membership concept is introduced. Proportionate adaptive filters can improve the convergence speed for the identification of sparse systems as compared to their conventional counterparts. Set-membership filtering (SMF) combine a bounded error specification...
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