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After completing this module, the students will be able to describe, calculate, sketch, analyze, evaluate, and transform continuous- and discrete-time as well as real and complex signals and systems in their deterministic forms and mathematical properties in both time and frequency domains. Furthermore, students acquired well-founded knowledge of classical unilateral and bilateral integral transforms in signal theory, including their inverses and mathematical properties. The students are able to apply their acquired skills autonomously to typical problems of signal processing, on paper as well as in MATLAB.

Continuous-time and discrete-time signals, linear time-invariant systems (LTI systems), convolution, convolutional integral and sum, impulse response of LTI systems, stability and causality, periodic signals, orthogonal function systems, continuous-time Fourier Series (FS), continuous-time Fourier Transformation (FT), Fourier integral, relationship between FS and FT, corresponding FT pairs, amplitude modulation and signal reconstruction, linear differential equations and transfer functions, Bode diagram, introduction to filters, discrete-time Fourier Transformation (DTFT), linear difference equations, discrete-time filters, sampling theorem, sampling and reconstruction of signals, sampling in frequence domain, Laplace Transformation (LT), convergence properties of the LT, z Transformation (ZT), residue theorem, discrete Fourier Transformation (DFT).

Differential and integral calculus, complex analysis, sets, differential equations, basic programming knowledge The following modules should be completed before registering for this module: - Analysis 1 - Analysis 2 - System Theory

In addtion to the students' individual lerarning methods, it is intended that students actively take part in the exercises, improving their knowledge through the discussion of solutions. The teaching method is based on direct lectures and global exercise lessons (discussion of solutions to posed problems). Additionally, collaborative tutor sessions are offered on the material. By means of supplementing practical programming tasks, the students are familiarized with the practical aspects of signal processing and are introduced to programming in MATLAB. Going along with the exercises of the practical programming there will be voluntary homework, that will not be included to the grade of the module.

The knowledge-based learning outcomes are tested in a 90-minute written exam. The lecture and exercises will account for 80% of the exam. The remaining 20% will be covered by topics related to the practical course. In total, up to 20% of the exam can be tested by means of multiple choice tasks. Students are only allowed to bring the lecture script incl. hand-written notes within it, a blank transparent sheet as well as drawing and writing material (no own paper!).