Adaptive filtering for non-gaussian stable processes

Abstract

A large class of physical phenomenon observed in practice exhibit non-Gaussian behavior. In this letter, a-stable distributions, which have heavier tails than Gaussian distribution, are considered to model non-Gaussian signals. Adaptive signal processing in the presence of such a noise is a requirement of many practical problems. Since direct application of commonly used adaptation techniques fail in these applications, new algorithms for adaptive filtering for α-stable random processes are introduced.