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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. Moreover, in this algorithm, the combination of the partial-update with set-membership focus on updating a selected subset of the filter coefficients at every iteration because the computational complexity is proportional to the number of filter coefficients. The resulting algorithm capitalizes not only from the sparse updating related to the set-membership framework but also from the partial update of the coefficients, reducing the average computational complexity. Simulations show that its overall complexity is lower compared to the affine projection algorithm based on set membership, its performance is close to that of its the conventional counterpart.
Image and Signal Processing (CISP), 2010 3rd International Congress on (Volume:9 )
Date of Conference: 16-18 Oct. 2010