Modules

Prerequisites

Contents

The course introduces bases of advanced signal processing methods in electrical power engineering. Introducing lectures provide ideas of discrete representations of continuous signal with basic functions and signal orthogonal projection. Next stage of the course concerns continuous representations of deterministic signals. Introduced definitions allow passing into nonparametric time-frequency representations. Then, follow the time-scale representations with wavelets. Backgrounds of statistical signal processing are introduced with outlined parameter estimation, optimal filtering, linear modeling and estimation. Finally, various methods of parametric spectrum estimation are outlined. Examples of application in electrical engineering are presented throughout the course. Main chapters: 1) The backgrounds of deterministic signal representations, 2) Basic functions and signals orthogonal projections, 3) Continuous representations of deterministic signals, 4) Nonparametric time-frequency representations, 5) Generalized equation of nonparametric time-frequency representations, 6) Time-scale signal representations, 7) Backgrounds of Statistical Signal Processing 8) Linear modeling and estimation of model parameters from data 9) Parametric spectrum estimation, 10) Applications in power systems.

Learning outcomes

Students will get a deeper insight into modern signal processing problems. The course is future-oriented, as few of the presented ideas are applied in power system nowadays.

Assessment

• Written examination, 90 min or • verbal examination, 30 min

Remarks

The lecture will be offered by Dr. Janik and Dr. Leonowicz as a one week block