TensorFlow and Escape Rooms

The last two days (Monday and Tuesday, September 16 and 17, 2019), the whole DSS team did a course on TensorFlow and Keras. Since we already have interfaces of TensorFlow to our real-time tool KiRAT, it was time now to extend our knowledge on graphs and the corresponding training of weights, biases, etc. After two days of hard work we booked two escape rooms and solved the "secrets" hidden in the rooms. It was really fun (both the TensorFlow workshop and the escape rooms, of course) and we enjoyed the time. Actually, we can really recommend this combination.

Basic Idea of RED

RED (robust and efficient DSP) is a collection of algorithms that should help engineers to implement basic signal processign tasks in - as the name states - a robust and efficient way. This includes mainly numerical aspects. An overview about the RED collection can be found here.

 

 

Here you can find the chapter on robust recursive norm computations as a single pdf file. If you would like to download all chapters please go to the RED overview page and get the pdf document that contain all chapters from there.

 

Authors of this Section:

Katharina Rebbe
Gerhard Schmidt
Owe Wisch

 

Related Downloads:

Pdf file of this section
   
Matlab script for a computing vector norms in an efficient and robust manner.

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

Recent News

DSS-Retreat 2019

As in the last year we spent a couple of days (15.10.2019 till 18.10.2019) on the island Sylt to reflect our past, current, and future research work. Due to a "cold wave" we were a bit reduced this year, but anyhow, we had a very good (and producive) time on this beautiful island. Beside our research plans (reflecting the last year and planning of the next years), we also discussed teaching ...


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