Robust adaptive filtering algorithms for impulsive noise environments

Abstract

In this thesis, robust adaptive filtering algorithms are introduced for impulsive noise environments which can be modeled as o;-stable distributions and/or c-contarninated Gaussian distributions. The algorithms are devcrloped using the Fractional Lower Order Statistics concept. Robust perf()rrnance is obtained.