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OverviewThis work introduces a new method for analysing measured signals: nonlinear mode decomposition, or NMD. It justifies NMD mathematically, demonstrates it in several applications and explains in detail how to use it in practice. Scientists often need to be able to analyse time series data that include a complex combination of oscillatory modes of differing origin, usually contaminated by random fluctuations or noise. Furthermore, the basic oscillation frequencies of the modes may vary in time; for example, human blood flow manifests at least six characteristic frequencies, all of which wander in time. NMD allows us to separate these components from each other and from the noise, with immediate potential applications in diagnosis and prognosis. Mat Lab codes for rapid implementation are available from the author. NMD will most likely come to be used in a broad range of applications. Full Product DetailsAuthor: Dmytro IatsenkoPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 2015 ed. Dimensions: Width: 15.50cm , Height: 1.10cm , Length: 23.50cm Weight: 3.672kg ISBN: 9783319200156ISBN 10: 3319200151 Pages: 135 Publication Date: 01 July 2015 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsIntroduction.- Linear Time-Frequency Analysis.- Extraction of Components from the TFR.- Nonlinear Mode Decomposition.- Examples, Applications and Related Issues.- Conclusion.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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