Adaptive filtering approaches for non-Gaussian stable processes
Date
1995-05
Advisor
Instructor
Source Title
1995 IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings
Print ISSN
0736-7791
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
1400 - 1403
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
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.
Course
Other identifiers
Book Title
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