Distributed Nonlinear System Identification in $\alpha$ -Stable Noise.

In this letter, a novel diffusion Volterra (DV) algorithm is proposed for distributed in-network system identification in the presence of $\alpha$ -stable noise. The proposed algorithm is based on the logarithmic least mean $p$ th-power criterion, which makes it robust against impulsive interferences, at the price of increased complexity. To overcome this shortcoming, we further develop the diffusion interpolated Volterra algorithm, which provides computational savings and good performance in comparison with the DV algorithm. Simulations results show that the proposed adaptive algorithms achieve better performance than the state-of-the-art approaches for distributed nonlinear system identification in impulsive noise. [ABSTRACT FROM AUTHOR]