M
Michel P. Tcheou
Researcher at Rio de Janeiro State University
Publications - 25
Citations - 253
Michel P. Tcheou is an academic researcher from Rio de Janeiro State University. The author has contributed to research in topics: Adaptive filter & Signal. The author has an hindex of 6, co-authored 23 publications receiving 213 citations. Previous affiliations of Michel P. Tcheou include Federal University of Rio de Janeiro.
Papers
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Journal ArticleDOI
The Compression of Electric Signal Waveforms for Smart Grids: State of the Art and Future Trends
Michel P. Tcheou,Lisandro Lovisolo,Moises V. Ribeiro,Eduardo A. B. da Silva,Marco A. M. Rodrigues,João Marcos Travassos Romano,Paulo S. R. Diniz +6 more
TL;DR: The main compression techniques devised for electric signal waveforms are reviewed providing an overview of the achievements obtained in the past decades and some smart grid scenarios emphasizing open research issues regarding compression of electric signalWaveforms are envisioned.
Journal ArticleDOI
An Inertial Algorithm for DC Programming
TL;DR: Numerical experiments on large-scale (nonconvex and nonsmooth) image denoising models show that the proposed algorithm outperforms the classic one in this particular application, specifically in the case of piecewise constant images with neat edges such as QR codes.
Journal ArticleDOI
Optimum Rate-Distortion Dictionary Selection for Compression of Atomic Decompositions of Electric Disturbance Signals
TL;DR: This letter addresses rate-distortion-optimum compression of signals from electric power system disturbances, using atomic decompositions, using several parameterized dictionaries to find the best compromise between the quantization of the coefficients in the atomic decomposition and its number of terms.
Journal ArticleDOI
Modeling of electric disturbance signals using damped sinusoids via atomic decompositions and its applications
Lisandro Lovisolo,Michel P. Tcheou,Eduardo A. B. da Silva,Marco A. M. Rodrigues,Paulo S. R. Diniz +4 more
TL;DR: The disturbance signal is modeled using a linear combination of damped sinusoidal components which are closely related to the phenomena typically observed in power systems.
Journal ArticleDOI
Audio Soft Declipping Based on Constrained Weighted Least Squares
TL;DR: A cost function is introduced consisting of a weighted sum of squared discrete cosine transform coefficients of the recovered signal, whose weights are obtained from the distorted signal itself and, thus, can adapt to different signal characteristics.