13M031OSZ - Knowledge-based Signal Processing

Course specification
Course title Knowledge-based Signal Processing
Acronym 13M031OSZ
Study programme Electrical Engineering and Computing
Module Audio and Video Communications
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition basic digital signal processing course
    The goal Objective of the course is to present knowledge-based signal processing concept. The focus is on analysis of signals and systems by methods of knowledge-based signal processing. Goal is application of the knowledge-based signal processing to selected classes of problems related to telecommunications and audio systems.
    The outcome Student will be able to understand knowledge-based signal processing, understand basic concepts of artificial intelligence, 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 of lectures Signal representations for numerical processing, computer-aided algorithm design and rearrangement, blackboard systems for knowledge-based signal understanding, integrated processing and understanding of signals, signal abstraction concept for signal interpretation, applications of knowledge-based signal processing related to telecommunication and audio systems.
    Contents of exercises Application of knowledge-based signal processing to typical problems related to telecommunications and 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
    3 1
    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
    Colloquia 20
    Seminars 50