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- François Auger, Patrick Flandrin
- IEEE Trans. Signal Processing
- 1995

Abstruct-In this paper, the use of the reassignment method, first applied 15 years ago by Kodera, Gendrin, and de Villedary to the spectrogram, is generalized to any bilinear time-frequency or time-scale distribution. This method creates a modified version of a representation by moving its values away from where they are computed, so as to produce a better… (More)

Huang’s data-driven technique of Empirical Mode Decomposition (EMD) is presented, and issues related to its effective implementation are discussed. A number of algorithmic variations, including new stopping criteria and an on-line version of the algorithm, are proposed. Numerical simulations are used for empirically assessing performance elements related to… (More)

- P. Abry, P. Flandrin, M. S. Taqqu
- 1999

Long-range dependence-Scaling phenomena-(Multi)fractal-Wavelet analysis Scaling analysis-Scaling parameters estimation-Robustness-Fractional Brownian motion synthesis-Fano factor-Aggregation procedure-Allan variance.

- Patrick Flandrin
- IEEE Trans. Information Theory
- 1992

- Patrick Flandrin, Gabriel Rilling, P. Goncalves
- IEEE Signal Processing Letters
- 2004

Empirical mode decomposition (EMD) has recently been pioneered by Huang et al. for adaptively representing nonstationary signals as sums of zero-mean amplitude modulation frequency modulation components. In order to better understand the way EMD behaves in stochastic situations involving broadband noise, we report here on numerical experiments based on… (More)

- Gabriel Rilling, Patrick Flandrin, Paulo Gonçalves, Jonathan M. Lilly
- IEEE Signal Processing Letters
- 2007

The empirical mode decomposition (EMD) has been introduced quite recently to adaptively decompose nonstationary and/or nonlinear time series. The method being initially limited to real-valued time series, we propose here an extension to bivariate (or complex-valued) time series that generalizes the rationale underlying the EMD to the bivariate framework.… (More)

- María Eugenia Torres, Marcelo A. Colominas, Gastón Schlotthauer, Patrick Flandrin
- 2011 IEEE International Conference on Acoustics…
- 2011

In this paper an algorithm based on the ensemble empirical mode decomposition (EEMD) is presented. The key idea on the EEMD relies on averaging the modes obtained by EMD applied to several realizations of Gaussian white noise added to the original signal. The resulting decomposition solves the EMD mode mixing problem, however it introduces new ones. In the… (More)

- Richard G. Baraniuk, Patrick Flandrin, Augustus J. E. M. Janssen, Olivier J. J. Michel
- IEEE Trans. Information Theory
- 2001

The generalized entropies of Rényi inspire new measures for estimating signal information and complexity in the time–frequency plane. When applied to a time–frequency representation (TFR) from Cohen’s class or the affine class, the Rényi entropies conform closely to the notion of complexity that we use when visually inspecting time–frequency images. These… (More)

- Wolfgang Martin, Patrick Flandrin
- IEEE Trans. Acoustics, Speech, and Signal…
- 1985

Abstmct-The Wigner-Ville spectrum has been recently introduced as the unique generalized spectrum for time-varying spectral analysis. Its properties are revised with emphasis on its central role in the analysis of second-order properties of nonstationary random signals. We propose here a general class of spectral estimators of the Wigner-Ville spectrum:… (More)

- Gabriel Rilling, Patrick Flandrin
- IEEE Transactions on Signal Processing
- 2008

This paper investigates how the empirical mode decomposition (EMD), a fully data-driven technique recently introduced for decomposing any oscillatory waveform into zero-mean components, behaves in the case of a composite two-tones signal. Essentially two regimes are shown to exist, depending on whether the amplitude ratio of the tones is greater or smaller… (More)