Conjugate Gradient Algorithm with Data Selective Updating

This paper applies data selective updating to the Modified Conjugate Gradient algorithm. In search for a new conjugategradient-like filtering algorithm, two different approaches are developed: the first one results in the recently proposed set-membership affine projection (SM-AP) algorithm and the second one reduces the computational requirements of the modified congujate gradient algorithm while keeping approximately the same good results in terms of convergence speed and misadjustment. Simulation results for a system identification experiment show the claimed performance with a considerable reduced number of updates.