Robust adaptive filtering algorithms for impulsive noise environments
Çetin, A. Enis
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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.
Fractional Lower Order Moments
e-contaminated Gaussian distributions