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Comparison of adaptive mono-component decompositions
Qian T.1; Li H.2; Stessin M.3
2013-04-01
Source PublicationNonlinear Analysis: Real World Applications
ISSN1468-1218
Volume14Issue:2Pages:1055-1074
Abstract

As presented in some recent publications, adaptively choosing the parameters of a Takenaka-Malmquist (TM) system according to the given signal gives rise to the so called adaptive Fourier decomposition (AFD). Besides optimal selections of the parameters to ensure the maximal energy gain at each step, AFD produces entries of non-negative analytic instantaneous frequency. The latter enables us to define a reasonable time-frequency distribution with most desired properties. The energy principle together with the unwinding process through factorizing out the inner function factors yields two variations of the standard AFD, both having appeared in the literature. They are referred by this paper as, respectively, unwinding adaptive Fourier decomposition (UAFD) and double sequence unwinding adaptive Fourier decomposition (DSUAFD). After a short summary of the three adaptive decompositions, the present paper makes comparison between them, as well as with the traditional Fourier series decomposition (FD). The related Dirac type time-frequency distributions associated with mono-components and mono-component decompositions of multi-components are introduced with examples. As necessary preparation we recall the concept mono-component and related knowledge in the introduction section.

KeywordAdaptive Fourier Decomposition Dictionary Inner Function Maximal Selection Principle Nevanlinna Factorization Theorem Orthogonal Greedy Algorithm Outer Function Reproducing Kernel
DOIhttps://doi.org/10.1016/j.nonrwa.2012.08.017
URLView the original
Indexed BySCI
Language英语
WOS Research AreaMathematics
WOS SubjectMathematics, Applied
WOS IDWOS:000312114400011
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Cited Times [WOS]:17   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF MATHEMATICS
Affiliation1.Department of Mathematics, Faculty of Science and Technology, University of Macau, Taipa, Macao, China
2.School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430074, China
3.Department of Mathematics and Statistics, University of Albany (SUNY), NY 12222, United States
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Qian T.,Li H.,Stessin M.. Comparison of adaptive mono-component decompositions[J]. Nonlinear Analysis: Real World Applications,2013,14(2):1055-1074.
APA Qian T.,Li H.,&Stessin M..(2013).Comparison of adaptive mono-component decompositions.Nonlinear Analysis: Real World Applications,14(2),1055-1074.
MLA Qian T.,et al."Comparison of adaptive mono-component decompositions".Nonlinear Analysis: Real World Applications 14.2(2013):1055-1074.
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