Publisher description for Signal processing with alpha-stable distributions and applications / Chrysostomos L. Nikias, Min Shao.

Bibliographic record and links to related information available from the Library of Congress catalog

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The recent explosion in the speed and power of computers has now made available the much more accurate, non-Gaussian models in signal processing algorithms. This book offers, for the first time, a full and lucid introduction to a very useful type of these non-Gaussian models, namely those specified by alpha-stable distributions.
Signal Processing with Alpha-Stable Distributions and Applications presents a long-awaited survey of the statistical properties, methods, and applications of symmetrical alpha-stable distributions. Its emphasis on practical rather than theoretical aspects will appeal to both researchers and practicing engineers in signal processing. Major topics covered in this comprehensive resource include:
Statistical methods in signal processing, including both the Gaussian and alpha-stable models
The stable distribution, its characterization and statistical properties
Fractional lower-order moments
Covariation and statistical conditional expectation of symmetric alpha-stable random variables
Methods for estimating the parameters of a stable distribution from sample data
Three conventional methods for estimating covariations: fractional lower-order moment estimator, the screened ratio estimator, and the least-squares estimator
Methods for estimating MA, AR, and ARMA model parameters
Methods for modeling impulsive signals
Designing and implementing optimum and suboptimum signal detectors in the presence of impulsive noise
Overview of current applications and future research trends of alpha-stable distributions for signal processing problems

Library of Congress subject headings for this publication:
Signal processing -- Mathematics.
Distribution (Probability theory)