Course Catalog 2006-2007

SGN-2406 SPECTRUM ESTIMATION AND ARRAY SIGNAL PROCESSING, 4 cr
Spectrum Estimation and Array Signal Processing

Courses persons responsible
Ioan Tabus

Lecturers
Ioan Tabus

Lecturetimes and places
Per II: Tuesday 10 - 12, TB215
Per II: Thursday 12 - 14, TB215

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

Objectives
Teach the student about spectrum estimation methods and their applications to speech-, audio- and array-processing.

Content
Content Core content Complementary knowledge Specialist knowledge
1. Periodogram and correlogram.
 
     
2. Nonparametric spectrum analysis.       
3. Filter-bank approach.       
4. Parametric methods for line spectra.       
5. Rational spectral models, Spatial methods.       

Requirements for completing the course
Final exam.

Evaluation criteria for the course

  • Course is graded on the basis of answers to exam questions. Very good grade is obtained when exam questions are correctly answered and accepted project work. Course acceptance threshold is half of the maximum exam points.

  • Used assessment scale is numeric (1-5)

  • Study material
    Type Name Auhor ISBN URL Edition, availability... Exam material Language
    Book "Introduction to Spectral Analysis" Stoica, P. & Moses, R.     Prentice Hall, 1997 No  English 
    Research           No  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.

    Remarks

  • The course is suitable for postgraduate studies.

  • Distance learning

  • ITC utilized during the course

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

  • Estimate as a percentage of the implementation of the course
  • - Contact teaching: 30 %
    - Distance learning: 0 %
    - Proportion of a student's independent study: 70 %

    Scaling
    Methods of instructionHours
    Lectures 48
    Exercises 24

    Other scaledHours
    Preparation for exam 25
    Exam/midterm exam 3
    Total sum 100

    Correspondence of content
    8001352 Spectrum Estimation and Array Signal Processing

    Course homepage

    Last modified 02.02.2006
    Modified byAntti Niemistö