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Bootstrap Techniques for Signal Processing (Hardcover)

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$135.45
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Description


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 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.


Product Details
ISBN: 9780521831277
ISBN-10: 052183127X
Publisher: Cambridge University Press
Publication Date: May 6th, 2004
Pages: 232
Language: English
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Created At: 11/4/2015 02:10pm
Last Updated At: 5/4/2022 06:26am