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BOOTSTRAP TECHNIQUES FOR SIGNAL PROCESSING
Asignalprocessing practitioner often asks themselves, “How accurate is my
parameter estimator?” There may be no answer to this question if an ana-
lytic analysis is too cumbersome and the measurements sample is too small.
The statistical bootstrap, an elegant solution, re-uses the original data with
acomputer 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 selec-
tion. The theory presented 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 ap-
plications to real-world problems in areas such as radar, sonar, biomedical
engineering and automotive engineering.
Abdelhak Zoubir is Professor of Signal Processing at Darmstadt Univer-
sity of Technology, Germany. He held positions in industry and in academia
in Germany and Australia. He has published over 180 technical papers in
the field of statistical methods for signal processing. He has maintained
his research interest in the bootstrap since the late 1980s. He also regularly
gives courses and tutorials on the bootstrap and its application for engineers.
D. Robert Iskander received a . degree in signal processing from
Queensland University of Technology (QUT), Australia, and holds the posi-
tion of a principal research fellow in the Centre for Health Research, QUT.
He has published over 60 technical papers in the field of statistical signal
processing and its application to optometry. He also has several patents in
the area of visual optics.
BOOTSTRAP TECHNIQUES FOR
SIGNAL PROCESSING
ABDELHAK M. ZOUBIR
D. ROBERT ISKANDER
cambridge university press
Cambridge, New York, Melbourne, Madrid