Physical presence required! Registration from 7:30 a.m. Note the COVID-19 precaution measures: Keep your distance, wear a mask.
Participation in a fire safety exercise is mandatory for all students whose study programme contains laboratory work. Admittance to lab work only after participation in this fire drill.
08:00 am - 09:00 am lecture
09:00 am - 11:00 am practical fire protection exercises outdoors, so please wear weatherproof clothing and sturdy shoes!

German Language Classes in cooperation with Goethe-Institut und Fremdsprachenzentrum Bremen. Registration link to follow soon.

Dieser Kurs knüpft an das Modul Digitale Signalverarbeitung an und behandelt fortgeschrittene Themen der digitalen Signalverarbeitung wie die diskrete Fouriertransformation (DFT), ihre Anwendungen, lineare Schätzprobleme und die Spektralschätzung.

The date for the initial organisational meeting of this lab, including grouping, will be advertised shortly. Room NW1 N1250.

The ICT lab consists of multiple parts, which are organized by two departments: the RF department and the dept. of communications engineering. Please refer to the individual departments for further information:

http://www.hf.uni-bremen.de/
http://www.ant.uni-bremen.de/courses/ictlab/

Course information www.fremdsprachenzentrum-bremen.de/1509.0.html?&L=1

Course information www.fremdsprachenzentrum-bremen.de/1509.0.html?&L=1

Course information www.fremdsprachenzentrum-bremen.de/1509.0.html?&L=1

Course information www.fremdsprachenzentrum-bremen.de/1509.0.html?&L=1

Übung am Ende des Semsters als Blockveranstaltung. Details und Datum werden zu Beginn des Semesters besprochen.

Block course at the end of the lecture period. Lecturer: Dr. Andreas Schenck

Anzahl der Teilnehmer ist begrenzt.

Elective course for M.Sc. CIT, Electrical Engineering & Information Technology and Space-ST. Block course at the end of the lecture period in February 2021.
Contents:
• Why swarm exploration – some motivational examples with applications in space and on Earth
• Preliminaries: selected mathematical formalism (vector spaces, matrices, representation and approximations in vector spaces, least squares, convex optimization)
• Recap of probability and statistics (calculus of probabilities, moments, Bayesian theory)
• Machine learning tools (supervised learning, linear regression, kernel methods, neural networks, impact of regularization, sparsity and compressed sensing)
• Models for multi-agent networks (connected network models, distributed inference strategies)
• Distributed machine learning and exploration (models for static spatial regression, information-theoretic exploration approaches, Bayesian sequential methods for learning and exploration)
• Discussion of several practical examples of swarm exploration solutions (cooperative localization, information-driven sparse mapping of magnetic fields, exploration of sparse gas sources using a swarm of mobile robots)
As outcome, the students should be able to:
• Understand key concepts in distributed information processing over networks,
• Explain and apply mathematical tools needed to implement classical machine learning algorithms in distributed settings

The students will learn about various research fields and applications of communication networks, which target the sustainable development goals (SDG) of the United Nations. The students will individually explore a given topic (with the help of research publications or other scientific materials) and prepare a presentation which will be discussed in class with the lecturer and the peers.

Registration for this lab must be done via Stud.IP.
The selection of participants will be done based on their grade in Control Theory I.
Please remember that this lab is in English. The preparation tasks therefore also have to be answered in English. Answers in German can not be accepted.

If there are questions, please contact H. Köhler (0421 218 62430).
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Anmeldung ausschließlich über Stud.IP..
Die Auswahl der Studenten erfolgt nach den Noten der Vorlesung Regelungstherie I.
Bitte denken Sie daran, dass dieses Labor in Englisch ist. Die Vorbereitungsaufgaben müssen daher auch auf Englisch beantwortet werden. Antworten auf Deutsch können nicht akzeptiert werden.

Bei Fragen kontaktieren Sie bitte H. Köhler (Telefon: 0421 218 62430).