Course detail

Signals and Systems

FEKT-CSISAcad. year: 2016/2017

The course Signals and Systems deals with fundamentals of analog and digital signal processing and system analysis, a topic that forms an integral part of engineering systems in many diverse areas. The course presents the basic principles for both continuous-time and discrete-time signals and systems. Signal representations are developed for both time and frequency domains. Basic types of signals and their properties, useful signal operations, as well as classification and analysis of systems, are discussed and illustrated. In addition, students become familiar with visualization and processing of signals using computer with standard signal software and gain practical experiences by use of laboratory devices such as oscilloscope, signal generator, signal analyzer, etc. Students will use gained knowledge in subsequent courses oriented to specific applications of signal processing.

Language of instruction

English

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

prof. Ing. Milan Sigmund, CSc.

Department

Department of Radio Electronics (UREL)

Learning outcomes of the course unit

The graduate is able
- to measure, display and describe signals,
- to define and generate required signal,
- to estimate spectrum and properties of signals,
- to convert analog signals and digital signals,
- to analyze systems,
- to discuss advantages and dis advantages of communication signals.

Prerequisites

Knowledge of bachelor mathematics is requested (derivations, integrals, solution of equations, fundamentals of probability analysis, statistical distributions).

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Techning methods include lectures, computer laboratories and practical laboratories. Course is taking advantage of e-learning (Moodle) system.

Assesment methods and criteria linked to learning outcomes

Students can obtain maximally 30 points for their activities during semester and 70 points for the final exam. The honored activities are as follows: one midterm test oriented to calculations of signal problems (10 points), five computer exercises (10 points) and five laboratory exercises (10 points). The written final exam is based on the theory of signals and systems as well as calculations (70 points).

Course curriculum

1. Introduction to the theory of signals and systems, basic signal operations in time domain, harmonic signal, function sinc(x), signal power and energy.
2. Periodic and nonperiodic signals, typical examples, rectangular pulses.
3. Fourier transform, basic properties, spectral function of selected signals.
4. Correlation and convolution, properties, application examples, interrelationship.
5. Continuous-time systems, Laplace transform, transfer function.
6. Analysis of continuous-time systems, linear and nonlinear systems.
7. Conversions between analog signals and digital signals, sampling, signal recovery.
8. Discrete Fourier transform, applications of DFT, principle of the FFT-algorithm.
9. Discrete-time systems, elementary system blocks, characteristics.
10. Analysis of discrete-time systems, testing signals.
11. Signals in random processes, stacionarity and ergodicity.
12. Signals and systems for data transmission in communication, modulations and demodulations.
13. Examples of signal processing in the fields of multimedia, medicine, and security.

Work placements

Not applicable.

Aims

The course is aimed to present common types of signals and their basic properties to students, and to explain analysis of systems as well as principles of interactions between signals and systems.

Specification of controlled education, way of implementation and compensation for absences

Computer exercises and laboratory exercises are compulsory. Missed lessons can be made up usually by the end of semester.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

KAMEN, E. W., HECK, B. S. Fundamentals of Signals and Systems. Englewood Cliffs: Prentice Hall, 2007. (EN)
MITRA, S. K. Digital signal processing. A computer-base approach. New York: The McGraw-Hill Companies, 2011. (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme EECC Bc. Bachelor's

    branch BC-EST , 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

prof. Ing. Milan Sigmund, CSc.

Syllabus

Signals. Examples, definition. Harmonic signal.
Periodic signals. Fourier series expansion. Properties.
Fourier Transform. Properties of the Fourier transform.
Linear time-invariant systems and their description. Filtering.
Continuous-time random signals.
Sampling and signal recovery. Digital signals.
Discrete-time signals. Discrete Fourier series.
Discrete Fourier transform. FFT.
Random sequences. Pseudorandom sequences. PSD.
Discrete-time systems. Z transform. Examples.
Communication systems. Baseband signals.
Amplitude modulation. Frequency modulation. ASK, FSK, PSK.
I-Q modulations. Multiplexing and multiple-access techniques.

Exercise in computer lab

13 hod., compulsory

Teacher / Lecturer

prof. Ing. Milan Sigmund, CSc.

Syllabus

Description of signals.
Fourier series expansion. Examples.
Properties of the Fourier transform.
Random signals. Sampling. Quantisation noise.
Discrete Fourier transform.
Amplitude and frequency modulation, keying.

Laboratory exercise

13 hod., compulsory

Teacher / Lecturer

prof. Ing. Milan Sigmund, CSc.

Syllabus

Introduction.
Spectral analysis of the periodic signals.
Amplitude and frequency modulation. Analysis of the random signal.
Sampling, aliasing.
Digital signal processing of the own speech.
The frequency response of the discrete-time system.