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Bootstrap Techniques for Signal Processing

Bootstrap Techniques for Signal Processing


  • Date Published: May 2004
  • availability: Available
  • format: Hardback
  • isbn: 9780521831277

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About the Authors
  • 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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    Reviews & endorsements

    '… an excellent text for a graduate level engineering course or a useful reference for those who wish to apply bootstrap techniques in their work.' Annals of Biomedical Engineering

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    Product details

    • Date Published: May 2004
    • format: Hardback
    • isbn: 9780521831277
    • length: 232 pages
    • dimensions: 255 x 180 x 18 mm
    • weight: 0.625kg
    • contains: 41 b/w illus. 34 tables
    • availability: Available
  • Table of Contents

    1. Introduction
    2. The bootstrap principle
    3. Signal detection with the bootstrap
    4. Bootstrap model selection
    5. Real data bootstrap applications
    Appendix 1. MATLAB codes for the examples
    Apendix 2. Bootstrap MATLAB toolbox

  • Authors

    Abdelhak M. Zoubir, Technische Universität, Darmstadt, Germany
    Abdelhak M. Zoubir received the Dipl.-Ing degree (BSc/BEng) from Fachhochschule Niederrhein, Germany, in 1983, the Dipl.-Ing. (MSc/MEng) and the Dr.-Ing. (PhD) degree from Ruhr University Bochum, Germany, in 1987 and 1992, all in Electrical Engineering. Early placement in industry (Klöckner-Moeller and Siempelkamp AG) was then followed by Associate Lectureship in the Division for Signal Theory at Ruhr University Bochum, Germany. In June 1992, he joined Queensland University of Technology where he was Lecturer, Senior Lecturer and then Associate Professor in the School of Electrical and Electronic Systems Engineering. In March 1999, he took up the position of Professor of Telecommunications at Curtin University of Technology, where he was Head of the School of Electrical & Computer Engineering from November 2001 until February 2003. In February 2003 he took up the position of Professor in Signal Processing at Darmstadt University of Technology. Dr Zoubir's general research interest lies in statistical methods for signal processing with applications in communications, sonar, radar, biomedical engineering and vibration analysis. His current research interest lies in robust estimation and in bootstrap techniques for spectrum estimation and the modelling of non-stationary and non-Gaussian signals. He was the General Co-Chairman of the Third IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) held in Darmstadt in December 2003, the Technical Chairman of the 11th IEEE Workshop on Statistical Signal processing held in Singapore in August 2001 and Deputy Technical Chairman (Special Sessions/Tutorials) of ICASSP-94 held in Adelaide. He served as an Associate Editor of the IEEE Transactions on Signal Processing from 1999 until 2005 and is currently Associate Editor of the EURASIP journals Signal Processing and the Journal of Applied Signal Processing. Dr Zoubir is a Member of the IEEE SPS Technical Committees on Signal Processing Theory and M

    D. Robert Iskander, Griffith University, Queensland
    D. Robert Iskander received his Ph.D. from Queensland University of Technology. He is currently a senior lecturer in the School of Engineering at Griffith University, Australia. He is also a visiting research fellow in the Centre for Eye Research at Queensland University of Technology. He has published over 50 technical papers, in fields such as statistical signal processing, visual optics, and ophthalmic instrumentation.

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