Course content

The course focuses on basic tools in analysis of analogue and digital signals and systems. Time and frequency domain description of signals. Use of Laplace, Fourier, and Z-transforms. Basic analogue and digital filter design, frequency response, data sampling. Excitation-response analysis of linear systems. Description and analysis of stochastic signals and measured signals with noise, correlations and energy spectrum analysis. Analysis of signals and systems using mathematical methods involving differential and integral calculus, as well as numerical methods using Matlab or python.

Learning outcome

The student is expected to:

1. Obtain, through a combined theoretical and experimental approach to the subject, a fundamental understanding of signal processing and needed theoretical and mathematical background to describe signals and systems, experimental measurement signals and time series.

2. Learn how to analyze various problems in signal processing using mathematical methods involving differential and integral calculus, as well as ICT-based/numerical methods by using Matlab or python.

Learning methods and activities

Lectures, compulsory calculation and computer simulation exercises (MATLAB or python). The expected workload in the course is 225 hours.

Compulsory assignments

• Laboratory exercises

Recommended previous knowledge

Basic physics, mathematics and statistics.

Course materials

"Signals, Systems and Transforms" by C. L. Phillips, J. M. Parr and E. A. Riskin; lecture notes and problems to solve will be distributed on BB.

Credit reductions