Course Catalog 2007-2008

SGN-1656 SIGNAL PROCESSING LABORATORY, 5 cr
Signal Processing Laboratory

Courses persons responsible
Mikko Parviainen

Lecturers
Mikko Parviainen

Implementations
  Period 1 Period 2 Period 3 Period 4 Period 5 Summer
Exercise work 25 h/per 25 h/per 25 h/per 25 h/per 25 h/per -
(Timetable for academic year 2007-2008)

Objectives
The goal of the course is to train the students to use signal processing tools in practical problem solving, and to train independent problem solving skills.

Content
Content Core content Complementary knowledge Specialist knowledge
1. Four laboratory exercises. The students select from the available exercises those that suite their specific field of study and personal interest.       

Requirements for completing the course
Four laboratory exercises and their reporting.

Evaluation criteria for the course

  • To pass the course, it is required that four exercises have been returned and accepted.

  • Used assessment scale is passed / failed

    • Prerequisites
    Code Course Credits M/R
    SGN-2016 SGN-2016 Digital Linear Filtering I 5 Recommendable
    SGN-2506 SGN-2506 Introduction to Pattern Recognition 4 Recommendable
    SGN-3016 SGN-3016 Digital Image Processing I 5 Recommendable
    SGN-4010 SGN-4010 Speech Processing Methods 2 Recommendable

    Prequisite relations (Sign up to TUT Intranet required)

    Additional information about prerequisites
    Each exercise work can have its own additional prerequisities.

    Remarks

  • Partial passing of course must be in connection with the same round of implementation.

    • 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: 5 %
    - Distance learning: 5 %
    - Proportion of a student's independent study: 90 %

  • Description of the course implementation from ICT point of view

    • To pass the course, it is required that four exercises have been returned and accepted. There is no exam. Numerical grades are not given.

    Scaling
    Methods of instructionHours
    Lectures 1.5
    Laboratory assignments 128
    Total sum 129.5

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

  • The students work independently on the laboratory exercises. Guidance is provided by the teachers responsible for each exercise.

    • Correspondence of content
    8006153 Signal Processing Laboratory

    Course homepage

    Last modified 17.08.2007
    Modified bySari Peltonen