DE LA O SERNA, JOSE ANTONIO
INGENIERÍA · Nivel 2
Desde 2018 es Lecturer en Universidad de Monterrey (UDEM)
José Antonio de la O Serna was born in San Pedro, Coahuila, Mexico in 1953. He received his Ph.D. degree from Telecom ParisTech, Paris, France, in 1982. In 1987 he joined the Ph.D. program in electrical engineering at the University...
José Antonio de la O Serna was born in San Pedro, Coahuila, Mexico in 1953. He received his Ph.D. degree from Telecom ParisTech, Paris, France, in 1982. In 1987 he joined the Ph.D. program in electrical engineering at the
University of Nuevo León (UANL), where he was a member of the Doctoral Committee. Currently he is research professor at the UANL, Monterrey, Mexico. He was also a Professor at Monterrey Institute of
Technology from 1982 to 1986. From 1988 to 1993, he was with the Electrical Department at the Polytechnic School in Yaoundé, Cameroon. Mr. de la O Serna is member of the Mexican Research System.
| Nombre | JOSE ANTONIO DE LA O SERNA |
|---|---|
| Área | INGENIERÍAS Y DESARROLLO TECNOLÓGICO |
| Campo | INGENIERÍA |
| Disciplina | INGENIERÍA ELÉCTRICA |
| Especialidad | TELECOMUNICACIONES |
| CVU | 15296 |
| Institución |
SIN INSTITUCIÓN
|
|---|---|
| Dependencia | NO APLICA |
| Entidad | NO APLICA |
| Nivel | 2 |
| Vigencia | Inicio: 01/01/2023 |
| Fin: 31/12/2037 | |
| Categoría: | EXTENSION 15 AÑOS |
Últimas publicaciones Scopus
- 2025
- Bessel and cosine filtering approaches for electromechanical modes identification International Journal of Electrical Power and Energy Systems · Vol. 170 Article
- Web-based wide-area monitoring platform for ringdown and clustering analytics in power systems International Journal of Electrical Power and Energy Systems · Vol. 169 Article
- Assessment of Harmonic Network Impedance based on Transient Harmonic Signals measured at an Industrial Power System IEEE Power and Energy Society General Meeting Conference Paper
- 2024
- Verifying the effectiveness of a Taylor–Fourier filter bank-based PPG signal denoising approach using machine learning Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing Book Chapter
- 2023
- Power quality harmonic monitoring by the O-splines-based multiresolution signal decomposition Monitoring and Control of Electrical Power Systems Using Machine Learning Techniques Book Chapter
