LJK Laboratory : Publications of Sylvain Meignen

Publications

2023

Q.Legros, D. Fourer, S. Meignen and M. Colominas,"Instantaneous Frequency and Amplitude Estimation in Multi-Compoent Signals Using an EM-based Algorithm", IEEE Transactions on Signal Processing, 2023.

J. Miramont, F. Auger, M.A. Colominas, N. Laurent and S. Meignen, "Unsupervised Classification of the Spectrogram Zeros with an Application to Signal Detection and Denoising", Signal Processing, 2023.

S. Meignen and M. Colominas, "A New Ridge Detector Localizing Strong Interference in Multicomponent Signals in the Time-Frequency Plane", IEEE Transactions on Signal Processing, 2023.

N. Laurent, S. Meignen, M. A. Colominas, J. Miramont, and F. Auger, "A novel approach based on Voronoï cells to classify spectrogram zeros of multicomposante signals ", ICASSP 2023.

M. Colominas and S. Meignen, "Making Synchrosqueezing Locally Adaptive in the Time-Frequency Plane", ICASSP 2023.

2022

Meignen, N. Laurent and T. Oberlin, " One or Two Ridges? An Exact Mode Separation Condition for the Gabor Transform", IEEE Signal Processing Letters, vol. 29, pp. 2507-2511, 2022.

N. Laurent, S. Meignen and M. A. Colominas , " On Local Chirp Rate Estimation in Noisy Multicomponent Signals: With an Application to Mode Reconstruction", IEEE Transactions on Signal Processing, vol. 70, pp. 3429-3440, 2022.

N. Laurent, S. Meignen, "A New Adaptive Technique for Multicomponent Signals Reassignment Based On Synchrosqueezing Transform", EUSIPCO 2022.

2021

S. Meignen and N. Singh, "Analysis of Reassignment Operators Used in Synchrosqueezing Transforms: with an Application to Instantaneous Frequency Estimation", IEEE Transactions on Signal Processing, vol. 70, pp.216-227, 2021 programs

N. Laurent and S. Meignen," A Novel Ridge Detector for Nonstationary Multicomponent Signals: Development and Application to Robust Mode Retrieval", IEEE Transactions on Signal Processing, vol. 69, pp. 3325-3336, 2021.programs

Q. Legros, J. Tachella, R. Tobin, A. McCarthy, S. Meignen, G. Buller, Y. Altmann, S. McLaughlin, M. Davies, "3D Reconstruction of Dynamic Scenes from Single-Photon Lidar", IEEE Transactions on Image Processing, vol. 30, pp. 1716-1727, 2021.

S. Meignen, D-H. Pham and M. Colominas, "On the Use of Short-Time Fourier Transform and Synchrosqueezing-Based Demodulation for the Retrieval of the Modes of Multicomponent Signals", Signal Processing, 107760, vol. 178, january 2021.programs

N. Laurent, S. Meignen, J. Fontecave-Jallon, B. Rivet, "A Novel Algorithm for Heart Rate Estimation Based on Synchrosqueezing Transform", EUSIPCO 2021.

N. Singh, S. Meignen, T. Oberlin, "Source Separation Based on Non-Negative Matrix Factorization of the Synchrosqueezing Transform", EUSIPCO 2021.

2020

N. Laurent and S. Meignen, "A Novel Time-Frequency Technique for Mode Retrieval Based on Linear Chirp Approximation", IEEE Signal Processing Letters, vol. 27, pp. 935-939, 2020. programs

Q. Legros, S. Meignen, Y. Altmann and S. McLaughlin, "Expectation-Maximization based approach to 3D reconstruction from single-waveform multispectral Lidar data", IEEE Transactions on Computational Imaging, vol. 6, pp. 1033-1043, 2020.

M. Colominas, S. Meignen and D-H. Pham, "Fully Adaptive Ridge Detection Based on STFT Phase Information", IEEE Signal Processing Letters, vol. 27, no. 1, pp. 620-624, 2020.

Q. Legros, S. Meignen, M. E. Davies, S. McLaughlin, Y. Altmann, "Robust depth imaging in adverse scenarios using single-photon Lidar and beta-divergences", SSPD 2020.

Q. Legros, S. Meignen, S. McLaughlin, Y. Altmann, "Stochastic EM algorithm for fast analysis of single waveform multi-spectral Lidar data", EUSIPCO 2020.

S. Meignen, M. Colominas, and D-H. Pham, "On the Use of Rényi Entropy for Optimal Window Size Computation in the Short-Time Fourier Transform", ICASSP 2020.

2019

S. Meignen, T. Oberlin and D-H. Pham, "Synchrosqueezing Transforms: from Low to High frequency Modulations and Perspectives", Comptes Rendus de l'Académie des Sciences, Fourier and the Science of today, vol. 20, no. 5, pp. 449-460, 2019.

S. Meignen, Q. Legros, Y. Altmann and S. McLaughlin, "A Novel Algorithm for the Identification of Dirac Impulses from Filtered Noisy Measurements", Signal Processing, vol. 162, pp. 268-281, 2019.

M. Colominas, S. Meignen and D-H. Pham, "Time-Frequency Filtering Based on Model Fitting in the Time-Frequency Plane", IEEE Signal Processing Letters, vol. 26, no. 5, pp. 660-664, 2019.

D-H. Pham and S. Meignen, "Demodulation Algorithm Based on Higher Order Synchrosqueezing", EUSIPCO 2019.

2018

S. Meignen and D-H. Pham, "Retrieval of the Modes of Multicomponent Signals from Downsampled Short-Time Fourier Transform", IEEE Transactions on Signal Processing, vol. 66, no. 23, pp. 6204-6215, 2018. programs

D-H. Pham, S. Meignen, Nafissa Dia, Julie Fontacave-Jallon and Bertrand Rivet, "Phonocardiogram Signal Denoising Based on Nonnegative Matrix Factorization and Adaptive Contour Representation Computation", IEEE Signal Processing Letters, vol. 25, no. 10, pp. 1475-1479, 2018.

R. Behera, S. Meignen, T. Oberlin, "Theoretical analysis of second order synchrosqueezing", Applied and Computational Harmonic Analysis, vol. 45, issue. 2, pp. 379-404, september 2018.

D-H. Pham and S. Meignen,"Second-order Synchrosqueezing Transform: The Wavelet Case, Comparisons and Applications", hal-01586372, 2018.

D-H. Pham and S. Meignen, "A novel thresholding technique for the denoising of multicomponent signals", ICASSP 2018.

2017

D-H. Pham and S. Meignen, "An Adaptive Computation of Contour Representations for Mode Decomposition", IEEE Signal Processing Letters, vol. 24, no. 11, pp. 1596-1600, 2017.

D. Fourer, F. Auger, K. Czarnecki, S. Meignen and P. Flandrin, "Chirp rate and instantaneous frequency estimation: application to recursive vertical synchrosqueezing", IEEE Signal Processing Letters, vol. 24, no. 11, pp. 1724-1728, 2017.

D-H. Pham and S. Meignen, " High-Order Synchrosqueezing Transform for Multicomponent Signals Analysis - With an Application to Gravitational-Wave Signal", IEEE Transactions on Signal Processing, vol. 65, no. 12, pp. 3168-3178, 2017. https://github.com/phamduonghung/FSSTn

S. Meignen, D-H. Pham and S. McLaughlin, "On Demodulation, Ridge Detection and Synchrosqueezing for Multicomponent Signals", IEEE Transactions on Signal Processing, vol. 65, no. 8, pp. 2093-2103, 2017. programs

D. Fourer, J. Harmouche, T. Oberlin, S. Meignen, F. Auger and P. Flandrin, "Chirp rate and instantaneous frequency estimation: application to recursive vertical synchrosqueezing", EUSIPCO 2017.

S. Meignen, T. Oberlin and S. McLaughlin, "Fully Adaptive Mode Decomposition from Time-Frequency Ridges", ICASSP 2017.

T. Oberlin and S. Meignen, "The second order synchrosqueezing wavelet transform", ICASSP 2017.

2016

S. Meignen, T. Oberlin, P. Depalle, P. Flandrin, and S. McLaughlin,"Adaptive multimode signal reconstruction from time-frequency representations", Philosophical Transactions of the Royal Society A, vol. 374, no. 2065, 2016.

R. Behera and S. Meignen, "Synchrosqueezing transform on an hyperbolic chirp", ICMAA 2016.

S. Meignen and B. Mateï, "Nonlinear and Nonseparable Bidimensional Multiscale Representation Based on Cell-Average Representation", MMCS 9, Tonsberg, Norway, 2016.

2015

B. Mateï and S. Meignen,"Nonlinear and Nonseparable Bidimensional Multiscale Representation Based on Cell-Average Representation",IEEE Transactions on Image Processing, vol. 24, no. 11,pp. 4570-4580, 2015.

T. Oberlin, S. Meignen and V. Perrier, "Second-order synchrosqueezing transform or invertible reassignment? Towards ideal time-frequency representations", IEEE Transactions on Signal Processing, vol. 63, no. 5, pp. 1335-1344, 2015.

S. Meignen, T. Oberlin and T. Gardner "Time-Frequency Ridge Analysis Based on Reassignment Vector", EUSIPCO 2015.

M. Kaaniche, B. Mateï and S. Meignen "Optimized Lifting Schemes Based on ENO Stencils for Image Approximation", ICIP 2015.

2014

T.Oberlin, S. Meignen and V. Perrier " The Fourier Based Synchrosqueezing Transform ", ICASSP 2014 .

2013

F. Auger, P. Flandrin, Y-T. Lin, S. McLaughlin, S. Meignen, T. Oberlin, H-T. Wu, "An Overview of Time-Frequency Reassignment and Synchrosqueezing",IEEE Signal Processing Magazine, vol. 30, no. 6, pp. 32-41, 2013. matlab code

B. Mateï, S. Meignen," A new Optimization Based Approach to the Empirical Mode Decomposition", Annals of the university of Bucharest, ,vol. 4, p. 129-139, 2013.

T.Oberlin, S. Meignen and S. McLaughlin" A Novel Time-Frequency Technique For Multicomponent Signal Denoising", EUSIPCO, 2013 .

T. Oberlin, S. Meignen and S. McLaughlin," Analysis of Strongly Modulated Multicomponent Signals with the Short-Time Fourier Transform", ICASSP, 2013.

2012

S. Meignen, T. Oberlin and S. McLaughlin,"A New algorithm for Multicomponent Signals Analysis based on SynchroSqueezing: With an Application to Signal Sampling and Denoising", IEEE Transactions on Signal Processing, vol. 60, no. 12, pp. 5787-5798, 2012. matlab code

B. Mateï, S. Meignen, "Nonlinear Cell-Average Multiscale Signal Representations: Application to Signal Denoising", Signal Processing, vol. 92, no. 11, pp. 2738-2746, 2012. matlab code

T. Oberlin, S. Meignen and V. Perrier, "An Alternative Formulation for the Empirical Mode Decomposition", IEEE Transactions on Signal Processing, vol. 60, no. 5, pp. 2236-2246, 2012. matlab code

B. Mateï, S. Meignen, "Analysis of a class of nonlinear and non-separable multiscale representations", Numerical Algorithms, vol. 60, no. 3, pp. 391-418, 2012.

B. Mateï, S. Meignen, "A new optimization based approach to the empirical mode decomposition", Annals of the University of Bucharest (mathematical series) - issue 1/2013, dedicated to the XIème Colloque Franco-Roumain de Mathématiques Appliquées, Buccarest, 2012.

T. Oberlin, S. Meignen and V. Perrier," On the Mode Synthesis in the Synchrosqueezing Method", EUSIPCO, 2012.

S. Meignen, T. Oberlin and S. McLaughlin,"Multicomponent Signal Denoising with SynchroSqueezing", IEEE SSP, 2012.

B. Mateï, S. Meignen, A. Zakharova, " Interpolatory Nonlinear and Non-Separable Multi-scale Representation: application to Image Compression", Proceedings of the 7th Conference on Curves and Surfaces, Volume 6920 of Lecture Notes in Computer Science, pages 473-487, Springer, 2012.

2011

C. Gérot , B. Mateï, S. Meignen, "Nonlinear and Non-Separable Multiscale Representations Based on Lipschitz Perturbation", Comptes Rendus Mathematique, vol. 349, no. 13–14, pp. 741-744, 2011.

B. Mateï, S. Meignen, A. Zakharova,"Smoothness Characterization and Stability of Nonlinear and Non-Separable Multiscale Representations", Journal of Approximation Theory, vol. 163, no. 11, pp. 1707-1728, 2011.

B. Mateï, S. Meignen, A. Zakharova, "Smoothness of Nonlinear and Non-separable Subdivision Schemes", Asymptotic Analysis, vol. 74, no. 3-4, pp. 229-247, 2011.

2010

C. Damerval, S. Meignen, "Study of a Robust Feature: the Pointwise Lipschitz Regularity",International Journal of Computer Vision, vol. 88, no. 3 , pp. 363-381, 2010.

P-Y. Guméry, J. Fontecave, E. Aithocine, S. Meignen, L. Heyer, P. Baconnier, "Modified Structural Intensity for Singularity Localization in Noisy Signals: Application to Coherent Averaging for Event-Synchronous ECG Interference Cancellation in Diaphragmatic EMG Signals", International Journal of Adaptive Control and Signal Processing, vol. 24, no. 5, pp. 424-433, 2010.

2009

C. Damerval and S. Meignen, "Highlight on a feature extracted at fine scales: the pointwise Lischitz regularity", Proceedings of the 2nd international conference on scale space and variational Methods, Volume 5567 of Lecture Notes in Computer Science, pages 782-794, Springer, 2009.

2007

S. Meignen, "Application of the Convergence of the Control Net of Box Splines to Scale-Space Filtering", IEEE Transactions on Image Processing, vol. 16, no. 11, pp. 2842-2848, 2007.

S. Meignen, V. Perrier, "A New Formulation for Empirical Mode Decomposition Based on Constrained Optimization", IEEE Signal Processing Letters, vol. 14, no. 12, pp. 932-935, 2007. scilab code

S. Meignen, P-Y. Guméry, "Reconstruction of Finite Signal Derivatives from Multiscale Extrema Representations: Application to Transient Estimation and Signal Approximation", IEEE Transactions on Signal Processing, vol . 55, no. 4, pp. 1554-1559, 2007.

C. Damerval, S. Meignen, "Blob Detection with Wavelet Maxima Lines", IEEE Signal Processing Letters, vol.14, no. 1, pp. 43-46, 2007.

S. Meignen et Valérie Perrier, "Une nouvelle formulation de la décomposition modale empirique fondée sur l'optimisation sous contraintes", congrés SMAI, 5 juin, 2007

C. Damerval and S. Meignen, "Computation of Blob-like Structures Characteristic Scale with Wavelet Maxima Lines", Sixth International conference on Curves and Surfaces, pp. 111-120, T2, Editors : P. Chenin, T. Lyche and L. Schumaker, 2007.

2006

S. Meignen, H. Meignen, "On the Modeling of Small Sample Distributions with Generalized Gaussian Density in a Maximum Likelihood Framework", IEEE Transactions on Image Processing, vol. 15, no. 6, pp. 1647-1652, 2006.

E. Aithocine, P-Y. Guméry, S. Meignen, L. Heyer, and S. B. Gottffried, " Contribution to Structural Intensity Tool: Application to the Cancellation of ECG Interfernce in Diaphragmatic EMG", IEEE BME Conference, New York, 2006.

2005

C. Damerval, S. Meignen and V. Perrier, "A fast Algorithm for Bidimensional EMD", IEEE Signal Processing Letters, vol. 12, no. 10, pp. 701-704, 2005.

S. Meignen, "Application of the Convergence of the Control Points of B-Splines to Wavelet Decomposition at Rational Scales and Rational Location", IEEE Signal Processing Letters, vol. 12, no. 1, pp. 29-32, 2005.

S. Meignen , S. Achard and P-Y. Guméry, "Time Localization of Transients with Wavelet Maxima Lines", IEEE Transactions on Signal Processing, vol. 53, no. 6, pp. 2251-2258, 2005.

P-Y Guméry, H. Roux-Buisson, S. Meignen, F.L. Comyn, M. Dematteis,B. Wuyam, J.L. Pépin and P.Levy, "An Adaptive Detector of Genioglossus EMG Reflex Using Berkner Transform for Time Latency Measurement in OSA Pathophysiological Studies ", IEEE Transactions on Biomedical Engineering, vol. 52, no. 8, pp. 1382-1389, 2005.

S. Meignen, "Characterization of Piecewise Smooth Images with Wavelets: Application to Noise Variance Estimation", rapport de recherche l'IMAG, RR 1075-M-200

2003

S. Meignen et P-Y Guméry ," Contribution au schéma hiérarchique de Berkner pour l'approximation de la transformée en ondelettes : application à la mesure du temps électromyographique du muscle génioglosse ", Revue Traitement du Signal, vol. 20, no. 4, pp. 375-388, 2003.

S. Meignen and V. Perrier,"Stable Feature Extraction Using Wavelet Filters for Texture Segmentation", rapport de recherche de l'IMAG, RR 1061-M-2003.

P-Y. Guméry, S. Meignen, H. Roux-Buisson, E. Aithocine and P. Levy, " Reconstruction Process of the Berkner Transform: Application to Scale Range Determintaion in a Genioglossal EMg Reflex Time-Scale Detector ", 25th Annual International Conference of the Engineering in Medicine and Biology Society, pp. 2606-2609, 2003, Cancun.

S. Meignen and V. Perrier, "Texture Segmentation Using Stable Texture Features", Proceedings of the 5th internationnal conference on curves and Surfaces, pp. 313-322, T2, Editors: A. Cohen, J.L. Merrien, L. Schumaker, 2003.

S. Meignen and P.Y. Guméry, "Application of Berkner transform to the detection and the classification of transients in EMG signals", Congrès de la SMAI-SMF, Nice 2003, poster.ppt

2002

S. Meignen and V. Perrier, "Texture scale and image Segmentation using Wavelet filters", fifth international conference on curves and surfaces, Saint-Malo, June 27-July 3, 2002. poster.ppt

S. Meignen and V. Perrier, "Unsupervised texture segmentation and texture scale definition", CEMRACS 2002, transparent.ps.gz

2001

J. Demongeot, J. Aracena, S. Ben Lamine, S. Meignen, A. Tonnelier, "Dynamical systems and biological regulation", Complex System, 2001

1999

A. Tonnelier, S. Meignen, H. Bosch, J. Demongeot, " Synchronization and desynchronization of neural oscillators", Neural Networks,vol. 12, pp. 1213-1228, 1999.

Seminars

S. Meignen, "Nonlinear and Non-Separable Multiscale Image Representation", Seminar of the institute for Digital Communications, School Engineering, Edinburgh, 10 december 2010.

S. Meignen, "Décomposition Modale Empirique: état de l'art et perspectives", Seminar of the GIPSA-Lab, 27 may 2010.

S. Meignen, "Signal Approximation in weak-IMF: A New Approach to Empirical Mode Decomposition", Third conference on the Hilbert-Huang Transform, Guangzhou, december 2008.

S. Meignen, "Présentation de l'algorithme EMD et perspectives", Seminar Paris-Nord, LT2I, 4 april 2007.

S. Meignen, "Utilisation de la convergence des points de contrôle des B-splines et des Box-splines pour l'approximation des transformées en ondelettes", Seminar Paris-Nord, LAGA, 12 january 2007.

S. Meignen, "Estimation of transients, signal approximation and blob detection with maxima lines", French-Romanian workshop on applied mathematics, LAMA, Chambéry, august 2006.