Bootstrap Techniques for Signal Processing (Paperback)

Language: English

Published by Cambridge University Press, Cambridge, 2007

0521034051 / 9780521034050

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Paperback. 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. The statistical bootstrap is a powerful tool in signal processing. This book covers the foundations of the bootstrap, its properties, its strengths, its limitations and model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Title
Bootstrap Techniques for Signal Processing (Paperback)
Author
Abdelhak M. Zoubir
Publisher
Cambridge University Press, Cambridge
Publication year
2007
Condition
new
Binding
Paperback
Language
English
ISBN 10
0521034051
ISBN 13
9780521034050
Edition
1st Edition

CitiRetail

Stevenage, United Kingdom

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AbeBooks seller since June 29, 2022

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