Abstract

The use of more accurate models in signal processing applications such as communications, radar, sonar, biomedical engineering, speech and image processing and machine learning has become a fundamental requirement. With an improved accuracy the models have become more complex and inferential statistical signal processing required in parameter estimation, signal detection and classification, for example, has become intractable. The signal processing practitioner requires a simple but accurate method for assessing errors of estimates and answering inferential questions. Asymptotic approximations are useful only when enough data is available, which is not always possible due to time constraints, the nature of the signal or the measurement setting. In place of the formulae and tables of parametric and non-parametric procedures based on complicated mathematics and asymptotic approximations, tools such as the bootstrap are powerful for solving complex engineering problems. It is the method of an engineer's choice for solving inferential signal processing problems, such as signal detection, confidence limits estimation and model selection, to mention a few. In this talk, we first give a brief overview of the basic principle underlying the bootstrap methodology. We then discuss bootstrap techniques for independent data, followed by bootstrap techniques for dependent data. Bootstrap methods for signal detection and model selection are presented along with frequency domain bootstrap methods for spectral analysis.

Speaker's Biography

Abdelhak M. Zoubir is a Fellow of the IEEE and IEEE Distinguished Lecturer (Class 2010- 2011). He received his Dr.-Ing. from Ruhr-Universitat Bochum, Germany in 1992. He was with Queensland University of Technology, Australia from 1992-1998 where he was Associate Professor. In 1999, he joined Curtin University of Technology, Australia as a Professor of Telecommunications. In 2003, he moved to Technische Universitat Darmstadt, Germany as Professor of Signal Processing and Head of the Signal Processing Group. His research interest lies in statistical methods for signal processing with emphasis on bootstrap techniques, robust detection and estimation and array processing applied to telecommunications, radar, sonar, automotive monitoring and safety, and biomedicine. He published over 400 journal and conference papers on the above areas. Dr. Zoubir served as General Chair and Technical Chair of numerous international IEEE conferences and workshops; more recently he was the Technical Co-Chair of ICASSP-14 held in Florence, Italy. He also served on publication boards of various journals, notably as Editor-In-Chief of the IEEE Signal Processing Magazine (2012-2014). Dr. Zoubir was the Chair (2010-2011) of the IEEE Signal Processing Society (SPS) Technical Committee Signal Processing Theory and Methods (SPTM). He served on the Board of Governors of the IEEE SPS and is the president of the European Association of Signal Processing (EURASIP).