Publicaciones en revistas científicas

Colominas, M. A., Meignen, S., & Pham, D. H. (2019). Time-Frequency Filtering Based on Model Fitting in the Time-Frequency Plane. IEEE Signal Processing Letters26(5), 660-664. DOI: 10.1109/LSP.2019.2904148

Colominas, M. A., Wens, V., Mary, A., Coquelet, N., Jomaa, M. E. S. H., Jrad, N., ... & Van Bogaert, P. (2019). Multichannel Time-Frequency Complexity Measures for the Analysis of Age-Related Changes in Neuromagnetic Resting-State Activity. IEEE journal of biomedical and health informatics. DOI: 10.1109/JBHI.2019.2892823

Restrepo, J. F., & Schlotthauer, G. (2018). Automatic estimation of attractor invariants. Nonlinear Dynamics91(3), 1681-1696.

Restrepo, J. F., & Schlotthauer, G. (2018). Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice. Complexity2018

Jomaa, M. E. S. H., Van Bogaert, P., Jrad, N., Kadish, N. E., Japaridze, N., Siniatchkin, M., ... & Humeau-Heurtier, A. (2018). Multivariate improved weighted multiscale permutation entropy and its application on EEG data. Biomedical Signal Processing and Control.

Colominas, M. A., Jomaa, M. E. S. H., Jrad, N., Humeau-Heurtier, A., & Van Bogaert, P. (2018). Time-Varying Time–Frequency Complexity Measures for Epileptic EEG Data Analysis. IEEE Transactions on Biomedical Engineering65(8), 1681-1688. DOI: 10.1109/TBME.2017.2761982

Sharma, R., Prasanna, S. R. M., Rufiner, H. L., & Schlotthauer, G. (2018). Detection of the glottal closure instants using empirical mode decomposition. Circuits, Systems, and Signal Processing37(8), 3412-3440.

Sharma, R., Vignolo, L., Schlotthauer, G., Colominas, M. A., Rufiner, H. L., & Prasanna, S. R. M. (2017). Empirical mode decomposition for adaptive AM-FM analysis of speech: A review. Speech Communication88, 39-64.

Humeau-Heurtier, A., Colominas, M. A., Schlotthauer, G., Etienne, M., Martin, L., & Abraham, P. (2017). Bidimensional unconstrained optimization approach to EMD: An algorithm revealing skin perfusion alterations in pseudoxanthoma elasticum patients. Computer methods and programs in biomedicine140, 233-239.

Alzamendi, G. A., & Schlotthauer, G. (2017). Modeling and joint estimation of glottal source and vocal tract filter by state-space methods. Biomedical Signal Processing and Control37, 5-15.

Colominas, M. A., Humeau-Heurtier, A., & Schlotthauer, G. (2016). Orientation-independent empirical mode decomposition for images based on unconstrained optimization. IEEE Transactions on Image Processing25(5), 2288-2297. DOI: 10.1109/TIP.2016.2541959

Restrepo, J. F., & Schlotthauer, G. (2016). Noise-assisted estimation of attractor invariants. Physical Review E94(1), 012212.

Colominas, M. A., Schlotthauer, G., & Torres, M. E. (2015). An unconstrained optimization approach to empirical mode decomposition. Digital Signal Processing40, 164-175.

Alzamendi, G. A., Schlotthauer, G., & Torres, M. E. (2015). State-space approach to structural representation of perturbed pitch period sequences in voice signals. Journal of Voice29(6), 682-692.

Leonarduzzi, R. F., Alzamendi, G. A., Schlotthauer, G., & Torres, M. E. (2015). Wavelet leader multifractal analysis of period and amplitude sequences from sustained vowels. Speech Communication72, 1-12.

Colominas, M. A., Schlotthauer, G., & Torres, M. E. (2014). Improved complete ensemble EMD: A suitable tool for biomedical signal processing. Biomedical Signal Processing and Control14, 19-29.

Restrepo, J. F., Schlotthauer, G., & Torres, M. E. (2014). Maximum approximate entropy and r threshold: A new approach for regularity changes detection. Physica A: Statistical Mechanics and its Applications409, 97-109.

Larrateguy, L. D., Milone, D., Di Persia, L., Schlotthauer, G., & Pais, C. (2014). Translational medicine in obstructive sleep apnea. European Respiratory Journal44(Suppl 58), P2267.

Antico, A., Schlotthauer, G., & Torres, M. E. (2014). Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: application to the Paraná River Basin. Journal of Geophysical Research: Atmospheres119(3), 1218-1233.

Alzamendi, G. A., Schlotthauer, G., Rufiner, H. L., & Torres, M. E. (2013). Evaluation of a new model for vowels synthesis with perturbations in acoustic parameters. Latin American Applied Research [Internet]43, 225-230.

Colominas, M. A., Schlotthauer, G., Torres, M. E., & Flandrin, P. (2012). Noise-assisted EMD methods in action. Advances in Adaptive Data Analysis4(04), 1250025.

Schlotthauer, G., Torres, M. E., & Jackson-Menaldi, M. C. (2010). A pattern recognition approach to spasmodic dysphonia and muscle tension dysphonia automatic classification. Journal of voice24(3), 346-353.

Schlotthauer, G., Torres, M. E., Rufiner, H. L., & Flandrin, P. (2009). EMD of Gaussian white noise: Effects of signal length and sifting number on the statistical properties of intrinsic mode functions. Advances in Adaptive Data Analysis1(04), 517-527.

Goddard, J., Schlotthauer, G., Torres, M. E., & Rufiner, H. L. (2009). Dimensionality reduction for visualization of normal and pathological speech data. Biomedical Signal Processing and Control4(3), 194-201.

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