Abstract: To filter out the non-Gaussian impulsive noises,a kernel fractional lower power (KFLP) algorithm based on the fractional lower order statistics error criterion was proposed.Due to the favorable characteristics of the fractional lower order power coefficient of reciprocal,the adaptive update of the weight vector will stop automatically in the pre-sence of impulsive interference.Thus,the effect of updating the weight vector caused by the impulse interference is eliminated.Simulation results show that as the power of the cost function approaches unity,the robustness of the kernel-type low-power algorithm improves in the non-Gaussian impulsive environment.Moreover,compared with the kernel least-mean-square (KLMS) algorithm based on the mean square error criterion,the proposed algorithm has smoother convergence curve and more stable performance.

Key words: Fractional lower order statistics error criterion, Kernel fractional low power algorithm, Kernel least-mean-square algorithm, Mean square error criterion, Non-Gaussian impulsive noise