Signal Processing

Continuous and discrete signals and systems in time and frequency domain with emphasis on discrete signals and systems. Sampling and aliasing. Nyquist sampling theorem. Analogue to digital (A/D) and digital to analogue (D/A) conversion. LTI systems, difference equations and convolution. FIR filters and IIR filters. Z-transform and pole-zero diagrams. Unit pulse response, frequency response and Discrete Fourier Transform (DFT). Leakage and window functions. Quantization. Application of computer assisted tools (MATLAB/Octave) and programming in signal processing.

Knowledge: Candidate shall

- be able to describe basic characteristics of continuous and discrete signals and be able to understand the relationship between time domain and frequency domain representation.

- be able to describe the properties of Linear Time Invariant (LTI) systems and how signals are affected by an LTI system.

- be able to describe methods to process and to analyze signals in time- and frequency domain.

- know how software can be used for modeling and processing signals and systems.

Skills: The candidate must be able to

- describe continuous and discrete signals in time and frequency domain.

- describe and analyze discrete LTI systems by employing unit pulse response and frequency response.

- calculate the output signal from a simple LTI system. - use of MATLAB/Octave to analyze and filter discrete signals.

- design digital filters by using MATLAB/Octave.

General competence: The candidate

- can study signals in time-and frequency domain and understand the connection between them.

- knows basic concepts and understands the relationship between signals and systems.

Lectures and independent exercises. The number of mandatory exercises is stated at the start of the semester. Mandatory exercises must be delivered according to specified deadlines and must be approved in order to take the exam.