The data-selective constrained affine-projection algorithm
نویسندگان
چکیده
This paper introduces a constrained version of the recently proposed set-membership affine projection algorithm based on the set-membershp criteria for coefficient update. The algorithm is suitable for linearly-constrained minimum-varianc filtering applications. The data selective property of the proposed algorithm greatly reduces the computational burden as compared with a nonselective approach. Simulation results show the good performance in terms convergence, final misadjustment, and reduced computational complexity.
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