MSc TC Thesis Presentation
- Wednesday, 14 February 2018
- EWI HB 17.150
Blind Signal IdentificationDennis van der Geest
The capability to efficiently find signals of interest in a very dense electromagnetic spectrum is becoming increasingly important with the continuous increase in spectrum usage. In this research project, methods are developed to identify communication signals by estimating signal features (symbol rate, modulation scheme, etc.) in the absence of a-priori knowledge, i.e. blind. By modelling the received communication signal both as a stationary and a cyclostationary process, various feature estimation methods are evaluated based on their computational complexity, their estimation accuracy and their robustness in the presence of signal contamination, such as frequency offsets. By efficiently combining various estimation methods, a signal classification algorithm is derived which is aimed to provide an optimal tradeoff between computational complexity and classification performance.Additional information ...
- Fri, 23 Feb 2018
- EWI HB 17.150
MSc CE Thesis Presentation
Energy Efficient Feature Extraction for Single-Lead ECG Classification Based On Spiking Neural Networks
Wearable system based on neuromorphic computing
- Wed, 7 Mar 2018
- Novio Tech Campus, Nijmegen, NL
Dutch Ultra Low Power Conference
The medicine of the future you’ll need to take only once, and it’s a bioelectronic one
The Dutch Ultra Low Power Conference brings together Belgian and Dutch professionals and companies involved in the development and application of devices with ultra low power technologies. It targets engineers, designers and technical managers in the advanced field of energy harvesting and ultra low power and energy-efficient designs. The keynote will be given by Wouter Serdijn, professor of bioelectronics at Delft University of Technology.