Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, S o Paulo

Cambridge University Press
The Edinburgh Building, Cambridge CB2 2RU, UK

Published in the United States of America by Cambridge University Press, New York

www.cambridge.org
Information on this title: www.cambridge.org/9780521831277

This publication is in copyright. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press.

First published in print format 2004

ISBN-13 978-0-511-19247-0 eBook (Adobe Reader)

ISBN-10 0-511-19247-9 eBook (Adobe Reader)

ISBN-10 0-521-83127-x hardback

Cambridge University Press has no responsibility for the persistence or accuracy of URLs for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.

Bootstrap Techniques for Signal Processing

A signal processing practitioner often asks themselves, How accurate is my parameter estimator? There may be no answer to this question if an analytic analysis is too cumbersome and the measurements sample is too small. The statistical bootstrap, an elegant solution, re-uses the original data with a computer to re-estimate the parameters and infer their accuracy.

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 presented in the book...