Marcelo Alejandro Colominas
Marcelo Alejandro Colominas
Researcher. CONICET and UNER, Argentina.
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Cited by
Cited by
A complete ensemble empirical mode decomposition with adaptive noise
ME Torres, MA Colominas, G Schlotthauer, P Flandrin
2011 IEEE international conference on acoustics, speech and signal …, 2011
Improved complete ensemble EMD: A suitable tool for biomedical signal processing
MA Colominas, G Schlotthauer, ME Torres
Biomedical Signal Processing and Control 14, 19-29, 2014
Noise-assisted EMD methods in action
MA Colominas, G Schlotthauer, ME Torres, P Flandrin
Advances in Adaptive Data Analysis 4 (04), 1250025, 2012
Empirical mode decomposition for adaptive AM-FM analysis of speech: A review
R Sharma, L Vignolo, G Schlotthauer, MA Colominas, HL Rufiner, ...
Speech Communication 88, 39-64, 2017
An unconstrained optimization approach to empirical mode decomposition
MA Colominas, G Schlotthauer, ME Torres
Digital Signal Processing 40, 164-175, 2015
Fully adaptive ridge detection based on STFT phase information
MA Colominas, S Meignen, DH Pham
IEEE Signal Processing Letters 27, 620-624, 2020
On the use of short-time fourier transform and synchrosqueezing-based demodulation for the retrieval of the modes of multicomponent signals
S Meignen, DH Pham, MA Colominas
Signal Processing 178, 107760, 2021
On the use of Rényi entropy for optimal window size computation in the short-time Fourier transform
S Meignen, M Colominas, DH Pham
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
Time-varying time–frequency complexity measures for epileptic eeg data analysis
MA Colominas, MESH Jomaa, N Jrad, A Humeau-Heurtier, P Van Bogaert
IEEE transactions on biomedical engineering 65 (8), 1681-1688, 2017
Orientation-independent empirical mode decomposition for images based on unconstrained optimization
MA Colominas, A Humeau-Heurtier, G Schlotthauer
IEEE Transactions on Image Processing 25 (5), 2288-2297, 2016
Time-frequency filtering based on model fitting in the time-frequency plane
MA Colominas, S Meignen, DH Pham
IEEE Signal Processing Letters 26 (5), 660-664, 2019
Decomposing non-stationary signals with time-varying wave-shape functions
MA Colominas, HT Wu
IEEE Transactions on Signal Processing 69, 5094-5104, 2021
Multivariate improved weighted multiscale permutation entropy and its application on EEG data
MESH Jomaa, P Van Bogaert, N Jrad, NE Kadish, N Japaridze, ...
Biomedical signal processing and control 52, 420-428, 2019
Voice jitter estimation using high-order synchrosqueezing operators
JM Miramont, MA Colominas, G Schlotthauer
IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 527-536, 2020
Bidimensional unconstrained optimization approach to EMD: An algorithm revealing skin perfusion alterations in pseudoxanthoma elasticum patients
A Humeau-Heurtier, MA Colominas, G Schlotthauer, M Etienne, L Martin, ...
Computer Methods and Programs in Biomedicine 140, 233-239, 2017
Descomposición empírica en modos por conjuntos completa con ruido adaptativo y aplicaciones biomédicas
MA Colominas, G Schlotthauer, P Flandrin, ME Torres
XVIII Congreso Argentino de Bioingeniería y VII Jornadas de Ingeniería …, 2011
Wave-shape function model order estimation by trigonometric regression
J Ruiz, MA Colominas
Signal Processing 197, 108543, 2022
On local chirp rate estimation in noisy multicomponent signals: With an application to mode reconstruction
N Laurent, MA Colominas, S Meignen
IEEE Transactions on Signal Processing 70, 3429-3440, 2022
Complete Ensemble EMD and Hilbert transform for heart beat detection
MA Colominas, G Schlotthauer, ME Torres
VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná …, 2015
Métodos guiados por los datos para el análisis de señales: contribuciones a la descomposición empírica en modos
MA Colominas
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