Course Catalog 2006-2007

SGN-2706 NONLINEAR SIGNAL PROCESSING, 5 cr
Nonlinear Signal Processing

Courses persons responsible
Moncef Gabbouj
Sari Peltonen

Lecturers
Moncef Gabbouj
Sari Peltonen

Lecturetimes and places
Per III,IV: Monday 14 - 16, TB224

Implementations
  Period 1 Period 2 Period 3 Period 4 Period 5 Summer
Lecture - - 2 h/week 2 h/week - -
Exercise - - 2 h/week 2 h/week - -
Exam  
(Timetable for academic year 2006-2007)

Objectives
Student will become familiar with some basic nonlinear filter techniques and will also know how and when to use them.

Content
Content Core content Complementary knowledge Specialist knowledge
1. review of estimation theory (maximum likelihood and M-estimators).       
2. median type filters.       
3. Filters based on robust estimation.  L-filter optimization.    
4. stack filters       
5. morphological filters and several other minor filter classes.       

Requirements for completing the course
Final examination.

Evaluation criteria for the course

  • Course is graded on the basis of answers to exam questions. Course acceptance threshold is approx. half the maximum exam points. Classroom exercise activity gives bonus points which are added to exam points.

  • Used assessment scale is numeric (1-5)

    • Study material
    Type Name Auhor ISBN URL Edition, availability... Exam material Language
    Book "Fundamentals of Nonlinear Digital Filtering" Astola, J. & Kuosmanen, P.     CRC Press, 1997 No  English 
    Lecture slides "Nonlinear Signal Processing" Kuosmanen, P.       Yes  English 

    Prerequisites
    Code Course Credits M/R
    SGN-1107 SGN-1107 Introductory Signal Processing 4 Mandatory
    SGN-1200 SGN-1200 Signal Processing Methods 4 Mandatory
    SGN-1250 SGN-1250 Signal Processing Applications 4 Recommendable

    Prequisite relations (Sign up to TUT Intranet required)

    Additional information about prerequisites
    Either SGN-1107 or SGN-1200 is required.

    Distance learning

  • ITC utilized during the course

    • - In information distribution via homepage, newsgroups or mailing lists, e.g. current issues, timetables
    - In compiling exercise, group or laboratory work
    - In distributing and/or returning exercise work, material etc

  • Estimate as a percentage of the implementation of the course

    • - Contact teaching: 50 %
    - Distance learning: 0 %
    - Proportion of a student's independent study: 50 %

    Scaling
    Methods of instructionHours
    Lectures 48
    Exercises 48

    Other scaledHours
    Preparation for exam 25
    Exam/midterm exam 3
    Total sum 124

    Principles and starting points related to the instruction and learning of the course

  • Normal lecture style. Slides available for copying before the lectures start.

    • Additional information related to course



    Correspondence of content
    8001453 Nonlinear Signal Processing

    Course homepage

    Last modified 21.08.2006
    Modified bySari Peltonen