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Title: Statistical analysis of synchrosqueezed transforms

Journal Article · · Applied and Computational Harmonic Analysis

Synchrosqueezed transforms are non-linear processes for a sharpened time–frequency representation of wave-like components. They are efficient tools for identifying and analyzing wave-like components from their superposition. This paper is concerned with the statistical properties of compactly supported synchrosqueezed transforms for wave-like components embedded in a generalized Gaussian random process in multidimensional spaces. Guided by the theoretical analysis of these properties, new numerical implementations are proposed to reduce the noise fluctuations of these transforms on noisy data. A MATLAB package SynLab together with several heavily noisy examples is provided to support these theoretical claims.

Research Organization:
Stanford Univ., CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
FC02-13ER26134/DE-SC0009409; SC0009409
OSTI ID:
1896340
Alternate ID(s):
OSTI ID: 1611205; OSTI ID: 1701852
Journal Information:
Applied and Computational Harmonic Analysis, Journal Name: Applied and Computational Harmonic Analysis Vol. 45 Journal Issue: 3; ISSN 1063-5203
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 31 works
Citation information provided by
Web of Science

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