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Completed Lecture Evaluations

We take the evaluation of our lectures, exercises, and labs very serious and we publish - as you can see below - all our evaluation results. Thus, we really appreciate if you take the time and fill out the evaluation forms that are distributed within our lectures.

Thank you to those of you who already participated in one of our evaluations.

Gerhard Schmidt

 

Adaptive Filters

Details Date of the evaluation Average mark of the lecture Average mark of the exercise Number of votings
Summer term 2021 1.3 1.2 15
Summer term 2020 1.5 1.2 14
Summer term 2019 1.7 2.3 14
Summer term 2017 1.5 1.7 13
Summer term 2016 1.7 1.5 9
Summer term 2015 1.9 2.0 4
Summer term 2013 1.7 1.6 5
Summer term 2012 1.4 2.1 9
Summer term 2011 1.4 1.7 2

 

 

The blue line shows the average mark of the lecture, the red line the one of the exercise.

Corresponding links:

  • Details of the lecture

 

Advanced Digital Signal Processing

Details Date of the evaluation Average mark of the lecture Average mark of the exercise Number of votings
Winter term 2021/2022 1.3 1.8 9
Winter term 2020/2021 1.7 1.9 12
Winter term 2019/2020 1.2 1.2 5
Winter term 2018/2019 1.3 1.9 9
Winter term 2017/2018 1.6 1.9 14
Winter term 2016/2017 1.3 1.4 1
Winter term 2015/2016 1.3 1.4 6
Winter term 2014/2015 1.5 2.3 4
Winter term 2013/2014 2.1 2.2 8
Winter term 2012/2013 2.0 2.4 5
Winter term 2011/2012 2.2 3.3 3
Winter term 2010/2011 1.3 1.9 2

 

The blue line shows the average mark of the lecture, the red line the one of the exercise.

Corresponding links:

  • Details of the lecture

 

Design Space Exploration for Unmanned Systems

No evaluations available yet.

Details of the lecture.

 

Digital Audio Effects

No evaluations available yet.

Details of the lecture.

 

Digital Signal Processing

Details Date of the evaluation Average mark of the lecture Average mark of the exercise Number of votings
Summer term 2021 1.3 1.7 7
Summer term 2020 1.7 1.6 9
Summer term 2019 1.7 1.6 5
Summer term 2017 1.6 1.2 5
Summer term 2016 1.3 1.7 3
Summer term 2015 1.4 2.0 2
Summer term 2014 1.6 2.0 7
Summer term 2013 1.7 1.9 14
Summer term 2012 1.7 1.6 5
Summer term 2011 1.7 2.1 4

 

The blue line shows the average mark of the lecture, the red line the one of the exercise.

Corresponding links:

  • Details of the lecture

 

Fundamentals of Acoustics

No evaluations available yet.

Details of the lecture.

 

Pattern Recognition and Machine Learning

Details Date of the evaluation Average mark of the lecture Average mark of the exercise Number of votings
Winter term 2021/2022 1.5 1.3 10
Winter term 2020/2021 1.8 1.9 16
Winter term 2019/2020 1.7 2.1 9
Winter term 2018/2019 1.5 2.1 10
Winter term 2017/2018 1.6 1.7 16
Winter term 2016/2017 1.6 1.8 11
Winter term 2015/2016 1.5 2.1 5
Winter term 2014/2015 1.4 1.4 8
Winter term 2013/2014 1.6 1.8 5
Winter term 2012/2013 1.8 1.8 5
Winter term 2011/2012 1.5 1.9 4
Winter term 2010/2011 1.7 2.1 3

 

The blue line shows the average mark of the lecture, the red line the one of the exercise.

Corresponding links:

  • Details of the lecture

 

Signals and Systems I

Details Date of the evaluation Average mark of the lecture Average mark of the exercise Number of votings
Summer term 2021 1.5 1.6 15
Summer term 2020 1.9 2.1 14
Summer term 2019 1.8 1.9 26
Summer term 2017 2.0 2.0 32
Summer term 2016 1.6 1.8 20
Summer term 2015 1.4 1.5 11
Summer term 2014 1.4 1.5 14
Summer term 2013 1.3 1.3 26
Summer term 2012 1.9 1.9 21
Summer term 2011 2.2 1.8 18

 

The blue line shows the average mark of the lecture, the red line the one of the exercise.

Corresponding links:

  • Details of the lecture

 

Signals and Systems II

Details Date of the evaluation Average mark of the lecture Average mark of the exercise Number of votings
Winter term 2021/2022 1.6 1.6 7
Winter term 2020/2021 1.3 1.9 16
Winter term 2019/2020 2.1 1.8 25
Winter term 2018/2019 2.3 2.2 25
Winter term 2017/2018 2.0 1.9 28
Winter term 2016/2017 1.8 2.1 16
Winter term 2015/2016 1.4 1.6 20
Winter term 2014/2015 1.8 1.9 10
Winter term 2013/2014 1.5 1.4 26
Winter term 2012/2013 1.3 1.3 26
Winter term 2011/2012 2.2 1.7 8
Winter term 2010/2011 2.1 1.7 14

 

The blue line shows the average mark of the lecture, the red line the one of the exercise.

Corresponding links:

  • Details of the lecture

 

Contact

Prof. Dr.-Ing. Gerhard Schmidt

E-Mail: gus@tf.uni-kiel.de

Christian-Albrechts-Universität zu Kiel
Faculty of Engineering
Institute for Electrical Engineering and Information Engineering
Digital Signal Processing and System Theory

Kaiserstr. 2
24143 Kiel, Germany

How to find us                              Imprint

  • A new podcast on our research on signal processing for underwater applications is online now. Liv Schnoor (previously Presser) interviewed Karoline Gussow, Bastian Kaulen, Gerhard Schmidt, and Owe Wisch on our latest research. It was really fun for us and the time (about on hour) was over really soon.

    If you like to listen to the podcast you can do that e.g. on Spotify (available for free). More about the podcast from Liv ("Was steckt dahinter") can be found e.g. on Liv's instagram page.