DS1SOS - Symbolic Signal Processing

Course specification
Course title Symbolic Signal Processing
Acronym DS1SOS
Study programme Electrical Engineering and Computing
Module Telecommunications and Information Technologies
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 9.0 Status elective
Condition
The goal Objective of the course is to present symbolic signal processing concept. The focus is on symbolic analysis of signals and systems. Goal is application of the symbolic signal processing to selected classes of problems related to telecommunications and audio systems.
The outcome Student will be able to understand symbolic signal processing, understand basic concepts of artificial intelligence and symbolic signal processing, related mathematical models, software tools for analysis and implementation discrete systems, identify and formulate problems that can be modeled as discrete systems and find efficient engineering solutions in telecommunications and audio systems.
Contents
Contents of lectures Signal representations for numerical processing, symbolic calculation, computer-aided algorithm design and rearrangement, symbolic analysis of signals and systems, morphological algorithms, signal abstraction concept for signal interpretation, applications of symbolic signal processing related to telecommunication and audio systems.
Contents of exercises Application of symbolic signal processing to typical problems related to telecommunications and audio signal processing.
Literature
1. 1. A.V. Oppenheim and S.H. Nawab, Symbolic and Knowledge-Based Signal Processing, Prentice Hall, 2000. (Original title)
2. 2. R. Maeder, Computer Science with Mathematica, Cambridge Univ.Press, 2000. (Original title)
3. 3. S. Wolfram, The Mathematica book, Wolfram media, Champaign, 2003. (Original title)
4. 4. M. Lutovac, D. Tošić, SchematicSolver (Original title)
5. 5. http://library.wolfram.com/infocenter/TechNotes/4814/, 2003. (Original title)
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
6
Methods of teaching lectures, exercises, homeworks
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 0 Test paper 30
Practical lessons 0 Oral examination 0
Projects 50
Colloquia 0
Seminars 20