| 19-12-2019 |
Reconstrucción de imágenes incompletas
Las imágenes submuestreadas son una manera de aumentar la velocidad de adquisición para la resonancia magnética. En este proyecto estudiaremos diferentes espacios en los cuales se pueden representar los datos de manera de facilitar su reconstrucción empleando algoritmos de Compressed Sensing.
Prerequisitos:
IEE2103
Tiene un método de evaluación Nota 1-7, con 10 créditos y tiene 2/3 vacantes disponibles |
Mentor(es): Ver en la plataforma |
| 07-06-2021 |
Study about the electrophysiological decoding of cognitive processes
This study will analyze the rhythmic activity of the electrophysiological signals produced by the brain, which is one of the most approachable manifestations of the brain activity underlying cognitive functions. One of the most important tasks in this approach is to select the relevant information and filter the environmental and internal noise. Therefore, an algorithm must be implemented that allows the raw data to be extracted and transformed into a signal that corresponds to the cognitive processes that are being evaluated. In this course, the student must implement algorithms for classification, decoding and description of the oscillatory activity of the EEG signal in humans, during the development of tasks that mainly assess memory and attention. For this we will use standard computational signal analysis tools.
Prerequisites:
None.
Evaluation method: Nota 1-7, with 0/1 available vacants |
Mentor(s): Open in the plataform |
| 03-05-2021 |
Keywords:
análisis de datos
señales fisiológicas
Prerequisites:
None.
Evaluation method: Nota 1-7, with 0/1 available vacants |
Mentor(s): Open in the plataform |
| 19-12-2019 |
Reconstruction of incomplete images
The images submuestreadas are a way to increase the speed of acquisition for the magnetic resonance imaging. In this project we will study different spaces in which they can represent the data in a manner to facilitate its reconstruction by employing algorithms of Compressed Sensing.
Prerequisites:
IEE2103
Evaluation method: Nota 1-7, with 2/3 available vacants |
Mentor(s): Open in the plataform |
| 19-07-2018 |
Prerequisites:
None.
Evaluation method: Nota 1-7, with 0/1 available vacants |
Mentor(s): Open in the plataform |
| 01-08-2016 |
Medical signals sonification
This project seeks, through data sonificiation, to improve clinical diagnosis.
Prerequisites:
IEE2103
Evaluation method: Nota 1-7, with 0/3 available vacants |
Mentor(s): Open in the plataform |