Sensor Systems

Fourier/Laplace Transform, Z-Transform, Mathematical basics in statistics and linear algebra.

• Basic algorithms in signal processing (1D and 2D), i.e: DFT, FFT, Chirp-Z, fast convolution, etc.;
• Images in spacial and frequency domain;
• statistical properties of images; color spaces;
• selected algorithms for feature extracting;
• least square estimation; random distributions; recursive estimation algorithms (i.e. Kalman);
• Project work with non-linear digital signal processing systems (e.g. beamforming system, non-linear system identification, ...)

• Students are able to apply fundamental techniques of digital signal processing in 1D and 2D in a target - specific way considering pros and cons of the individual techniques.
• They are able to condition sensor signals, to make statistical evaluations and interpret the results.
• They are able to handle basic methods and combinations of them to extract features of signals.
• They can estimate the reliability of the results.
  Students have experience in scientific approach of problem solving.

Lectures, calculation exercises, computer exercises, project work.

• Exam (50%) and
• Project (50%)

For a positive grade, a minimum of 50% of the possible points must be achieved in each part of the examination.

Not applicable

• Oppenheim, Alan V.; Willsky, Alan S.; Nawab, Syed Hamid (1997): Signals & systems. 2nd ed. Upper Saddle River, N.J: Prentice Hall (= Prentice-Hall signal processing series).
• Stark, Hans-Georg (2005): Wavelets and signal processing: an application-based introduction. Berlin; New York: Springer. Online im Internet: http://site.ebrary.com/id/10228999 (Zugriff am: 29.08.2016).
• Hoffmann, Josef; Quint, Franz (2012): Signalverarbeitung mit MATLAB und Simulink: anwendungsorientierte Simulationen. 2. Aufl. München: Oldenbourg.
• Meyer, Martin (2011): Signalverarbeitung. Wiesbaden: Vieweg+Teubner. Online im Internet: http://link.springer.com/10.1007/978-3-8348-8138-0 (Zugriff am: 08.02.2017).
• Gonzalez, Rafael C.; Woods, Richard E. (2018): Digital Image Processing. 4th edition. New York: Pearson.
• Sonka, Milan; Hlavac, Vaclav; Boyle, Roger (1993): Image processing, analysis, and machine vision. 1st ed. London; New York: Chapman & Hall Computing (= Chapman & Hall computing series).

face-to-face