Title:  Signals and Systems 

Code:  ISS 

Ac.Year:  2017/2018 

Term:  Winter 

Curriculums:  

Language:  Czech 

Public info:  http://www.fit.vutbr.cz/study/courses/ISS/public/ 

Credits:  6 

Completion:  examination (written) 

Type of instruction:  Hour/sem  Lectures  Sem. Exercises  Lab. exercises  Comp. exercises  Other 

Hours:  39  12  0  0  14 

 Examination  Tests  Exercises  Laboratories  Other 

Points:  51  25  0  12  12 



Guarantee:  Černocký Jan, doc. Dr. Ing., DCGM 

Lecturer:  Černocký Jan, doc. Dr. Ing., DCGM 
Instructor:  Baskar Murali K., DCGM Beneš Karel, Ing., DCGM Grézl František, Ing., Ph.D., DCGM Kodym Oldřich, Ing., DCGM Mošner Ladislav, Ing., DCGM Ondel Lucas, Mgr., DCGM Silnova Anna, DCGM Skácel Miroslav, Ing., DCGM Žmolíková Kateřina, Ing., DCGM 

Faculty:  Faculty of Information Technology BUT 

Department:  Department of Computer Graphics and Multimedia FIT BUT 

Prerequisites:  

Schedule:  Day  Lesson  Week  Room  Start  End  Lect.Gr.  St.G.  EndG. 

Tue  exercise  nahradni cviceni ISS  20171003  A113  10:00  11:50    
Tue  lecture  lectures  E112  15:00  17:50  2BIB   
Tue  lecture  lectures  E104  15:00  17:50  2BIB   
Tue  lecture  lectures  E105  15:00  17:50  2BIB   
Tue  lecture  lectures  E112  15:00  17:50  3BIT  xx  xx 
Tue  lecture  lectures  E112  15:00  17:50  2BIA  xx  xx 
Wed  exercise  lectures  G202  09:00  10:50  2BIA   
Wed  exercise  lectures  G202  09:00  10:50  2BIB   
Wed  exercise  lectures  M103  09:00  10:50  2BIB   
Wed  exercise  lectures  M103  09:00  10:50  2BIA   
Wed  exercise  lectures  G202  17:00  18:50  2BIB   
Wed  exercise  lectures  G202  17:00  18:50  2BIA   
Wed  exercise  lectures  M103  17:00  18:50  2BIA   
Wed  exercise  lectures  M103  17:00  18:50  2BIB   
Thu  exercise  lectures  M103  09:00  10:50  2BIA   
Thu  exercise  lectures  M103  09:00  10:50  2BIB   
Thu  exercise  lectures  M103  11:00  12:50  2BIB   
Thu  exercise  lectures  M103  11:00  12:50  2BIA   
Thu  exercise  lectures  M103  13:00  14:50  2BIB   
Thu  exercise  lectures  M103  13:00  14:50  2BIA   
Thu  exercise  lectures  M103  15:00  16:50  2BIB   
Thu  exercise  lectures  M103  15:00  16:50  2BIA   
Thu  exercise  lectures  M103  17:00  18:50  2BIB   
Thu  exercise  lectures  M103  17:00  18:50  2BIA   
Fri  exercise  lectures  A113  09:00  10:50  2BIB   
Fri  exercise  lectures  A113  09:00  10:50  2BIA   
Fri  exercise  lectures  A113  11:00  12:50  2BIA   
Fri  exercise  lectures  A113  11:00  12:50  2BIB   
Fri  lecture  v angličtině  lectures  E112  13:00  15:50  2BIA   
Fri  lecture  v angličtině  lectures  E104  13:00  15:50  2BIA   
Fri  lecture  v angličtině  lectures  E105  13:00  15:50  2BIA   
Fri  lecture  v angličtině  lectures  E112  13:00  15:50  3BIT  xx  xx 



Learning objectives: 

  To learn and understand basic theory of signals and linear systems with
continuous and discrete time. To introduce to random signals. The
emphasis of the course is on spectral analysis and linear filtering  2
basic building blocks of modern communication systems. 
Description: 

  Continuous and discrete time signals and systems. Spectral analysis in
continuous time  Fourier series and Fourier transform. Systems with
continuous time. Sampling and reconstruction. Discretetime signals and
their frequency analysis: Discrete Fourier series and Discretetime
Fourier transform. Discrete systems. Twodimensional signals and
systems. Random signals. 
Knowledge and skills required for the course: 

  basic maths and statistics 
Subject specific learning outcomes and competences: 

  Students will learn and understand basis of description and
analysis of discrete and continuoustime signals and systems. They will
also obtain practical skills in analysis and filtering in MATLAB. 
Generic learning outcomes and competences: 

  Students will deepen their knowledge in mathematics and statistics and
apply it on real problems of signal processing. During the course, they
will get acquainted with math and visualizationSW Matlab. 
Syllabus of lectures: 

  Digital filters  fundamentals and
practical usage
 Frequency analysis using DFT  fundamentals
and practical usage
 Image processing (2D signals)  fundamentals
and practical usage
 Random signals  fundamentals and
practical usage
 Applications of signal processing and
introduction to theory
 Frequency analysis of continuous time
signals
 Continuous time systems
 From continuous to discrete  sampling,
quantization
 Discrete signal sin more detail
 Digital filtering in more detail
 Random signals in more detail
 Applications and advanced topics of signal
processing

Syllabus of computer exercises: 

  Introduction to MATLAB
 Projection onto basis, Fourier series
 Processing of sounds
 Image processing
 Random signals
 Sampling, quantization and aliasing

Syllabus  others, projects and individual work of students: 

 The individual project aims at image processing, see http://www.fit.vutbr.cz/study/courses/ISS/public/#proj 
Fundamental literature: 


 Oppenheim A.V., Wilski A.S.: Signals and systems, Prentice Hall, 1997

Study literature: 

  http://www.fit.vutbr.cz/study/courses/ISS/public/
 Jan, J., Kozumplík, J.: Systémy, procesy a signály. Skriptum VUT v Brně, VUTIUM, 2000.
 Šebesta V.: Systémy, procesy a signály I., Skriptum VUT v Brně, VUTIUM, 1997.
 Jan J., Číslicová filtrace, analýza a restaurace signálů, VUT v Brně, VUTIUM, 2002, ISBN 8021415584.

Controlled instruction: 

   participation in computer labs is not checked but active
participation and presentation of results to the tutor is evaluated by
2 pts.
 Groups in computer labs are organized according to
inscription into schedule frames.

Progress assessment: 

   active participation in computer labs, presentation of results to the tutor  2 pts. each, total 12 pts.
 halfsemester exam, written materials, computers and calculators prohibited, 25 pts.
 submission of project report  12b.
 final exam  51 pts., written materials, computers and calculators prohibited, list of basic equations will be at your disposal. The minimal number of points which can be obtained from the final
exam is 17. Otherwise, no points will be assigned to the student.

