Course detail
Signals 2
FEKT-BKC-SI2Acad. year: 2019/2020
The subject is focused on the analysis and digital processing of signals from the field of telecommunication. It provides a theoretical basis of signal modulation, discrete linear transformations, description of random process and its characteristics. It also deals with the problems of filtration (FIR, IIR, adaptive, inverse), correlation and spectral analysis of signals, detection of signals in noise. Theory is complemented by introductory information on complex and multidimensional signals. The subject provides both theoretical background and practical verification. To this end, the Matlab programming environment will be used.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Knowledge of elements of signal and system theory, mathematics on Bc level, Matlab.
Co-requisites
Planned learning activities and teaching methods
Teaching methods include lectures and computer exercises. Student develops individual tasks during computer exercises.
Assesment methods and criteria linked to learning outcomes
Students will be evaluated for individual work (max. 20 points, min. 10 points) and final exam (max. 80 points, min. 20 points).
The student obtains the credit, who: i) submits all independent works and obtains at least 10 points.
The exam can be obtained on the basis of a written final exam: max. 80 points, min. 40 points. The written final exam consists of two parts, a numerical part and a theoretical part, and covers the content of lectures and exercises.
Course curriculum
1. Introduction to signal analysis.
2. Discrete signals.
3. Discrete linear transformations.
4. Discrete linear systems
5. Linear filtering of signals. FIR type filters
6. Type IIR filters
7. Signal representation.
8. Modulation
9. Random signals and their characteristics
10. Correlation analysis of signals
11. Spectral analysis of deterministic signals.
12. Spectral analysis of stochastic signals.
13. Cumulative methods of signal enhancement in noise
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
Linear signal filtering
FIR filters
IIR filters
Averaging methods of signal enhancement in noise
Complex signals and their applications
Frequency translation of signals
Correlation analysis of signals
Spectral analysis of deterministic signals
Spectral analysis of stochastic signals
Detection of signals in noise, plain inverse filtering
Restoration of signals, Wiener filter
Exercise in computer lab
Teacher / Lecturer
Syllabus
Linear signal filtering
FIR filters
IIR filters
Averaging methods of signal enhancement in noise
Complex signals and their applications
Frequency translation of signals
Correlation analysis of signals
Spectral analysis of deterministic signals
Spectral analysis of stochastic signals
Detection of signals in noise, plain inverse filtering
Restoration of signals