Nonlinear Mode Decomposition: Theory and Applications
This 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.
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Nonlinear Mode Decomposition: Theory and Applications
This 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.
109.99 In Stock
Nonlinear Mode Decomposition: Theory and Applications

Nonlinear Mode Decomposition: Theory and Applications

by Dmytro Iatsenko
Nonlinear Mode Decomposition: Theory and Applications

Nonlinear Mode Decomposition: Theory and Applications

by Dmytro Iatsenko

Paperback(Softcover reprint of the original 1st ed. 2015)

$109.99 
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Overview

This 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.

Product Details

ISBN-13: 9783319387123
Publisher: Springer International Publishing
Publication date: 07/03/2016
Series: Springer Theses
Edition description: Softcover reprint of the original 1st ed. 2015
Pages: 135
Product dimensions: 6.10(w) x 9.25(h) x 0.01(d)

Table of Contents

Introduction.- Linear Time-Frequency Analysis.- Extraction of Components from the TFR.- Nonlinear Mode Decomposition.- Examples, Applications and Related Issues.- Conclusion.
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