Diffusion Sign Subband Adaptive Filtering Algorithm for Distributed Estimation

The diffusion subband adaptive filtering algorithm has faster convergence rate than the diffusion least mean square algorithm. In the case where the measurement noise includes impulsive interferences, however, this algorithm may suffer from bad convergence performance. This letter proposes a diffusion sign subband adaptive filtering algorithm, which is derived based on the method of minimization of the l1-norm of the intermediate subband a posteriori error vector subject to a constraint on the intermediate estimate of the unknown vector at each agent in the network. Simulation results demonstrate that the proposed algorithm is robust against impulsive interferences.