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Bootstrap Methods and Applications : A Tutorial for the Signal Processing Practitioner

By Abdelhak M. Zoubir and D. Robert Iskander

Abstract

Given the wealth of literature on the topic supported by solutions to practical problems, we would expect the bootstrap to be an off-the-shelf tool for signal processing problems as are maximum likelihood and least-squares methods. This is not the case, and we wonder why a signal processing practitioner would not resort to the bootstrap for inferential problems. We may attribute the situation to some confusion when the engineer attempts to discover the bootstrap paradigm in an overwhelming body of statistical literature. Our aim is to give a short tutorial of bootstrap methods supported by real-life applications. This pragmatic approach is to serve as a practical guide rather than a comprehensive treatment, which can be found elsewhere. However, for the bootstrap to be successful, we need to identify which resampling scheme is most appropriate

Topics: 111303 Vision Science, bootstrap methods, resampling scheme, signal processing practitioner, statistical literature, signal sampling
Publisher: IEEE
Year: 2007
DOI identifier: 10.1109/MSP.2007.4286560
OAI identifier: oai:eprints.qut.edu.au:14131

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Citations

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