This page intentionally left blank 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
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