Adaptive filtering approaches for non-Gaussian stable processes
Çetin, A. Enis
1995 IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings
1400 - 1403
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A 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.
KeywordsHilbert space framework
Non Gaussian signals
Recursive least squares
Digital signal processing
Least squares approximations
Spurious signal noise
Published Version (Please cite this version)https://doi.org/10.1109/ICASSP.1995.480503
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