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Signals and Systems

Do you want to learn how signals and systems are used in signal and control engineering? The concepts of signals and systems are powerful tools for any engineer dealing with information-bearing, measurable physical quantities. Applications range from communications engineering, to signal processing, to control engineering. In this course programm you will learn the characteristic properties of various signals and systems.

  • Gain basic knowledge in the field of signal and control engineering
  • Flexible blended learning format
  • Study while you work

Dates / Location / Cost

DateLocation Costs
01.04.2022 - 30.09.2022
Course ID: UUL_SST_SaS_202204
Ulm & online 1.170,00 

Institution and Location


School of Advanced Professional Studies Ulm University


  • University of Ulm
  • online

Target Audience and Prerequisites

Target Audience

This course program is aimed at bachelor, diploma or state examination graduates with solid basic knowledge in an engineering subject, technical computer science or physics, who would like to deal intensively with issues relating to sensor technology and systems engineering.


Prerequisite is a first university degree e.g. bachelor, diploma, state examination etc. in a technical subject. Students should have solid knowledge of advanced mathematics at least on the level of a bachelor’s degree in engineering. Especially the topics linear algebra and analysis (series, functions, derivatives, integrals, complex numbers) are very important.

Content and Learning Objectives


  • basic properties of discrete-time and continuous-time systems
  • z-transformation
  • linear time-invariant systems, convolution integral
  • Fourier transformation, discrete Fourier transformation, Fourier series
  • sampling theorem
  • probability theory, random variables and stochastic processes
  • stochastic signals and linear time-invariant systems

Programme Details

The online study takes place in self-study and in the form of group work. For self-study, video lectures are available, which clearly present the course content, and a detailed script.

The reader-friendly script is prepared according to the didactic concept of the University of Ulm for part-time participants: it contains, for example, learning stops, multiple-choice questions, exercises, etc. Lecture notes and further materials and forums are available in a modern web-based e-learning environment.

Tutorials for solving problems and exercises are offered by a mentor typically bi-weekly and held via video conferences. These seminars will help the participants handling the exercises and working on the learning matters.

An online forum for exchange with the other participants will also be available.

Learning Objectives

After successful completion of the course program, students will be able to:

  • classify, interpret and compare signals and systems with respect to their characteristic properties
  • explain and apply analytical and numerical methods for the analysis and synthesis of signals and systems in the time and frequency domain
  • choose suitable signal transformations and calculate them with the help of transformation tables
  • recognize stochastic signals and analyze them according to their characteristic properties
  • calculate and interpret the influence of linear time-invariant systems on stochastic signals

Course Format, Certification, Quality Assurance

Course Format



Upon successful completion of the module, you will receive a certificate as well as a supplement that lists the contents of the module as an overview.


The course program requires a total of 180 hours of workload.

Creditpoints (ECTS)



Deutsch / English

Dates and Deadlines

Course Dates

The exact dates for the classroom sessions as well as the exam dates are yet to be announced.




  • Dr. Werner Teich, Institute of Communications Engineering, University of Ulm
  • Dipl.-Inf. Steffen Moser, Institute of Embedded Systems/Real-Time Systems, University of Ulm

Looking for a programme with a larger scope?

Check out other modules on the subject of Sensor Systems Engineering: