Robust Statistics For Signal Processing


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Robust Statistics for Signal Processing


Robust Statistics for Signal Processing

Author: Abdelhak M. Zoubir

language: en

Publisher: Cambridge University Press

Release Date: 2018-11-08


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Understand the benefits of robust statistics for signal processing using this unique and authoritative text.

Topics in Robust Statistical Signal Processing


Topics in Robust Statistical Signal Processing

Author: Kenneth Steven Vastola

language: en

Publisher:

Release Date: 1982


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This dissertation addresses several problems in robust signal processing. The term robust in this context implies insensitivity to small deviations from the assumed statistical description of the signal and/or noise. The first part of this thesis considers the problem of linear minimum-mean-square-error estimation of a stationary signal observed in additive stationary noise when knowledge of the signal spectrum and noise spectrum is inexact. In the second part of this dissertation, a previously developed cohesive theory of robust hypothesis testing in which uncertainty is modeled via 2-alternating Choquet capacity classes is considered in light of recent applications of this theory to problems in robust signal processing and communication theory.

Academic Press Library in Signal Processing


Academic Press Library in Signal Processing

Author: Mats Viberg

language: en

Publisher: Academic Press

Release Date: 2013-08-31


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This third volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in array and statistical signal processing. With this reference source you will: - Quickly grasp a new area of research - Understand the underlying principles of a topic and its application - Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved - Quick tutorial reviews of important and emerging topics of research in array and statistical signal processing - Presents core principles and shows their application - Reference content on core principles, technologies, algorithms and applications - Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge - Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic