On Instantaneous Frequency

By Norden E. Huang, Zhaohua Wu, Steven R. Long, Kenneth C. Arnold, Xianyao Chen, K. Blank. Advances in Data Science and Adaptive Analysis, 2009

662 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/6c59a590a4bfb9790d613d7c575b99767da46ff6

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In Analytical Chemistry

In Control and Systems Engineering

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Citations in the corpus

Synchrosqueezing-Based Recovery of Instantaneous Frequency from Nonuniform Samples (2010, methodology): “One of the most commonly used approaches for doing this can be described as follows [11].”
Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool (2011, methodology): “The EMD algorithm, first proposed in [2], made more robust as well as more versatile by the extension in [3] (allowing e.”
Comparison of methods for non-stationary hydrologic frequency analysis: Case study using annual maximum daily precipitation in Taiwan (2017, methodology): “…and this approach has been used to analyze various types of climate data (Xie et al., 2002; Duffy, 2005; Li and Davis, 2006; Wu et al., 2007; Pegram et al., 2008; McDonald et al., 2007; McMahon et al., 2008; Huang et al., 2009; Franzke, 2009; Lee and Ouarda, 2010, 2012; Chang et al., 2011).”
A time varying filter approach for empirical mode decomposition (2017, background): “In order to measure how much it deviates from the WAIF, we define a relative criteria rather than an absolute one ( ) ( ) ( ) Loughli avg nB t t t (39) When ( )t gets smaller, the bandwidth of the signal becomes smaller.”
Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks (2017, background): “This is because frequency is defined instantaneously, and depends on the gradient on the signal (Huang et al., 2009), which is theoretically defined at each time point.”
Empirical Mode Decomposition-Based Time-Frequency Analysis of Multivariate Signals: The Power of Adaptive Data Analysis (2013, methodology): “The amplitudes { ( )} a t m m 1 = and instantaneous frequencies { ( )} t m m 1 ~ = plotted against time yield a T-F-amplitude representation of the signal, termed the Hilbert–Huang spectrum (HHS) [19].”
The association between working memory precision and the nonlinear dynamics of frontal and parieto-occipital EEG activity (2022, methodology): “Therefore, the instantaneous phase can be obtained directly with the Hilbert transform or later proposed methods such as normalized Hilbert transform or direct quad-rature (DQ, Huang et al. 2009).”