The data-selective constrained affine-projection algorithm

This paper introduces a constrained version of the recently proposed set-membership affine projection algorithm based on the set-membership criteria for coefficient update. The algorithm is suitable for linearly constrained minimum-variance 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 of convergence, final misadjustment, and reduced computational complexity.