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 | 2505 | 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 | 1220 | 2014 |
Noise-assisted EMD methods in action MA Colominas, G Schlotthauer, ME Torres, P Flandrin Advances in Adaptive Data Analysis 4 (04), 1250025, 2012 | 182 | 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 | 86 | 2017 |
An unconstrained optimization approach to empirical mode decomposition MA Colominas, G Schlotthauer, ME Torres Digital Signal Processing 40, 164-175, 2015 | 39 | 2015 |
Fully adaptive ridge detection based on STFT phase information MA Colominas, S Meignen, DH Pham IEEE Signal Processing Letters 27, 620-624, 2020 | 32 | 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 | 28 | 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 | 26 | 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 | 25 | 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 | 20 | 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 | 16 | 2019 |
Decomposing non-stationary signals with time-varying wave-shape functions MA Colominas, HT Wu IEEE Transactions on Signal Processing 69, 5094-5104, 2021 | 14 | 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 | 14 | 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 | 13 | 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 | 12 | 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 | 11 | 2011 |
Wave-shape function model order estimation by trigonometric regression J Ruiz, MA Colominas Signal Processing 197, 108543, 2022 | 10 | 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 | 10 | 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 | 7 | 2015 |
Métodos guiados por los datos para el análisis de señales: contribuciones a la descomposición empírica en modos MA Colominas | 4 | 2016 |