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:
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An excellent introduction to a particular type of non-Gaussian signal processing which is specified by the stable distributions, focusing on their applications. Stresses the statistical properties, methods and uses of symmetric alpha-stable distributions, emphasizing their theoretical aspects. Includes an overview of the latest application developments and future trends of alpha-stable distributions, with a brief description of on-going work in detection, blind channel identification and deconvolution, robust beamforming, adaptive interference mitigation as well as their implementation to communications, sonar, radar and other engineering areas.
CHRYSOSTOMOS L. NIKIAS is Professor of Electrical Engineering Systems and Director of the Center for Research on Applied Signal Processing at the University of Southern California. He is also a member of the California Council on Science and Technology.
MIN SHAO is currently a staff scientist at HNC Software, Inc. and formerly worked at the University of Southern California.
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