Adaptive filtering approaches for non-Gaussian stable processes
Date
1995-05
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Source Title
1995 IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings
Print ISSN
0736-7791
Electronic ISSN
Publisher
IEEE
Volume
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Pages
1400 - 1403
Language
English
Type
Journal Title
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Volume Title
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39
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Abstract
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.
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Keywords
Hilbert space framework , Non Gaussian signals , Recursive least squares , Algorithms , Computer simulation , Digital filters , Digital signal processing , Least squares approximations , Optimization , Random processes , Recursive functions , Errors , Mathematical models , Signal processing , Signal theory , Spurious signal noise , Adaptive filtering , Additive noise , Alpha-stable process , Gaussian process