19D031SOS - Symbolic Signal Processing

Course specification
Course title Symbolic Signal Processing
Acronym 19D031SOS
Study programme Electrical Engineering and Computing
Module Telecommunications
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 9.0 Status elective
      Condition none
      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 or 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 or audio systems.
      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 or audio systems.
      Contents of exercises Application of symbolic signal processing to typical problems related to telecommunications or audio signal processing.
      1. 1. A.V. Oppenheim and S.H. Nawab, Symbolic and Knowledge-Based Signal Processing, Prentice Hall, 2000.
      2. 2. R. Maeder, Computer Science with Mathematica, Cambridge Univ.Press, 2000.
      3. 3. S. Wolfram, The Mathematica book, Wolfram media, Champaign, 2003.
      4. 4. M. Lutovac, D. Tošić, SchematicSolver
      5. 5., 2003.
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      Methods of teaching lectures, projects
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures 0 Test paper 0
      Practical lessons 0 Oral examination 30
      Projects 70
      Colloquia 0
      Seminars 0