Robust Multitask Diffusion Affine Projection M-Estimate Algorithm: Design and Performance Analysis

The distributed estimation performance of multitask diffusion affine projection (AP) algorithm (MD-APA) will be greatly reduced under the impulsive noise interference. To overcome this defect, a robust MD-APA is derived by using M-estimate function (MD-APM) to resist the impulsive noise interference. The mean performance, mean square performance and steady-state performance of MD-APM algorithm are studied, and the convergence range of the step-size and the theoretical steady-state MSD are obtained. In addition, the computational complexity of MD-APM algorithm is analyzed in detail. Simulation experiments show that the proposed MD-APM algorithm has better estimation performance compared with MD-APA and MD-APSA under the impulsive noise interference, and its theoretical steady-state mean square deviation (MSD) can provide accurate prediction.