Arıkan, OrhanBelge, MuratÇetin, A. EnisErzin, Engin2016-02-082016-02-081995-050736-7791http://hdl.handle.net/11693/27762Date of Conference: 9-12 May 1995Conference name: 1995 International Conference on Acoustics, Speech, and Signal ProcessingA large class of physical phenomenon observed in practice exhibit non-Gaussian behavior. In this paper, α-stable distributions, which have heavier tails than Gaussian distribution, are considered to model non-Gaussian signals. Adaptive signal processing in the presence of such kind of noise is a requirement of many practical problems. Since, direct application of commonly used adaptation techniques fail in these applications, new approaches for adaptive filtering for α-stable random processes are introduced.EnglishHilbert space frameworkNon Gaussian signalsRecursive least squaresAlgorithmsComputer simulationDigital filtersDigital signal processingLeast squares approximationsOptimizationRandom processesRecursive functionsErrorsMathematical modelsSignal processingSignal theorySpurious signal noiseAdaptive filteringAdditive noiseAlpha-stable processGaussian processConference Paper10.1109/ICASSP.1995.480503