# Signal Analysis

## Subject description

Introduction: Basic definitions, short history of the signal processing theory, position of the signal processing theory in electro technical and other sciences. Mathematical signal representations, signals classifications.

Signals representations: Use of the signals representations, types of representations and representations quality measures, examples of basic functions sequences.

Frequency analysis of periodical and non-periodical signals.

Random signals: Approaches to the random signal processing, stationary random process, deterministic descriptors

Signals correlation and convolution: Correlation and convolution definitions and properties on different types of signals,

Correlation and convolution applications in signal processing: Similarity measures, random signals spectrum evaluation, convolution and linear stationary systems, detection of periodic components in combination of signals.

Digital signal processing: Basic principles for digital signals acquisition and their properties. Frequency representation of digital signals, digital correlation and convolution.

## Objectives and competences

The aim of this course is to familiarize students with different types of signals and to present different approaches to signal description and processing. Students develop an understanding of the concepts used for signal representation and get acquainted with signal analysis techniques based on correlation and convolution. The course provides the theoretical basis for many practical problems in the fields of imaging technologies, speech technologies, pattern recognition, artificial intelligence and machine learning.

## Teaching and learning methods

• Lectures
• Interactive teaching
• Practical assignements

## Expected study results

After successful completion of the course, students should be able to:
define the main types of signals and methods for their description, representation, processing and analysis,

• recognize the main characteristics of signals and their transformations,
• develop procedures for the analysis of basic signals such speech or images,
• analyse problems that may be represented as linear timeinvariant systems,
• propose the most suitable methods for the description of signals given the requirements of selected application domains,
• explain the differences between continuous and discrete signals and corresponding processing methods and the importance of continuous and discrete signals for different applications.

## Basic sources and literature

1. MIHELIČ, France, ŠTRUC, Vitomir. Skripta za predmet Analiza signalov na študijskem programu Aplikativna elektrotehnika na stopnji VS UL FE. izd. Ljubljana: Fakulteta za elektrotehniko, 2012. http://luks.fe.uni-lj.si/sl/studij/AS/pub/skripta_analiza_signalov.pdf.
2. MIHELIČ, France, GYERGYÉK, Ludvik, EBENŠPANGER, Tomaž. Signali : priročnik z zbirko rešenih nalog. 4. popravljena in dopolnjena izd. Ljubljana: Založba FE in FRI, 2009. 132 str.
3. MIHELIČ, France. Signali. 1. izd. Ljubljana: Fakulteta za elektrotehniko, 2014. ISBN 978-961-243-054-2. http://luks.fe.uni-lj.si/nluks/wp-content/uploads/2014/11/Signali.pdf.

## Stay up to date

University of Ljubljana, Faculty of Electrical Engineering Tržaška cesta 25, 1000 Ljubljana