Disruptive functions and technology for angle-based integrated grid operation in converter-dominated power systems with predominantly renewable energy supply
DisrupSys
Disruptive functions and technology for angle-based integrated grid operation in converter-dominated power systems with predominantly renewable energy supply
Federal Ministry for Economic Affairs and Climate Action (BMWK); Duration: 2021 to 2024
Modern high-frequency systems benefit massively from machine learning methods. In applications where rule-based algorithms reach their limits, these data-driven approaches enable a significant increase in resolution and accuracy. This is exemplified by current research challenges, namely for the classification of targets in autonomous driving radar systems, radar-based gesture recognition for smart home applications and device control as well as in the field of medical technology for the contactless monitoring of human vital signs.
Performance accreditation:
m1785-2022 - Machine Learning in Electrical Engineering and Information Technology<ul><li>p1778-2022 - Machine Learning in Electrical Engineering and Information Technology: mündlich</li></ul>