Dr. Davood Babazadeh

Gastdozent

Kontakt

Dr. Davood Babazadeh
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Harburger Schloßstraße 36,
21079 Hamburg
Gebäude HS36, Raum C3 1.013
Tel: +49 40 42878
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TUHH Open Research (TORE)

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Lehrveranstaltungen

Stud.IP
zur Veranstaltung in Stud.IP Studip_icon
Machine Learning in Electromagnetic Compatibility (EMC) Engineering (VL)
Untertitel:
This course is part of the module: Machine Learning in Electrical Engineering and Information Technology
Semester:
SoSe 24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv3006_s24
DozentIn:
Prof. Dr. sc. techn. Christian Schuster, Dr. Cheng Yang
Beschreibung:

Electromagnetic Compatibility (EMC) Engineering dealswith design, simulation, measurement, and certification of electronic andelectric components and systems in such a way that their operation is safe,reliable, and efficient in any possible application. Safety is herebyunderstood as safe with respect to parasitic effects of electromagnetic fieldson humans as well as on the operation of other components and systems nearby.Examples for components and systems range from the wiring in aircraft and shipsto high-speed interconnects in server systems and wirless interfaces for brainimplants. In this part of the course we will give an introduction to thephysical basics of EMC engineering and then show how methods of MachineLearning (ML) can be applied to expand todays physcis-based approaches in EMCEngineering.

Leistungsnachweis:
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>
ECTS-Kreditpunkte:
1
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Theoretische Elektrotechnik (E-18)
In Stud.IP angemeldete Teilnehmer: 2