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  BOOTSTRAP TECHNIQUES FOR SIGNAL PROCESSING
 
 
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Author: Abdelhak M. Zoubir , D. Robert Iskander
Publisher: Cambridge University Press
Published: 1/11/2008
Pages 231 pages

Stock Status:In Stock
Availability:: Usually Ships in 24 to 48 Hours
Product Code: 9780521034050
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Description Table of Contents
 
The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.

• Describes a number of practical signal processing problems successfully solved with bootstrap techniques • Contains many MATLAB examples and tools • Shows how to choose suitable bootstrap models for different applications
 

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  0 of 0 people found the following review helpful:
 
Useless! February 26, 2009
Reviewer: Anonymous Person from new york, IN United States  
While the boostrap is a nice statistical toy, I doubt it will ever have any use in a real world signal processing system.
The danger with this technique, beside the fact that Dr. Zoubir makes it his life's work, is its misuse.
I would strongly advise against teaching this to signal-processing undergraduate students.
Save you money, buy a comic book instead.

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