Course Catalog 2007-2008

SGN-2506 INTRODUCTION TO PATTERN RECOGNITION, 4 cr
Introduction to Pattern Recognition

Courses persons responsible
Ulla Ruotsalainen
Jussi Tohka

Lecturers
Jari Niemi

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 2007-2008)

Objectives
The goal is to introduce basic methods and principles of pattern recognition.

Content
Content Core content Complementary knowledge Specialist knowledge
1. Basics of multivariate probability and statistics, class conditional density function, Bayesian decision theory.       
2. Estimation of the parameters of the density function from training data.       
3. Nonparametric techniques for estimation of the density function and pattern classification.       
4. Algorithms for unsupervised classification.       

Requirements for completing the course
Final examination and active participation in exercises.

Evaluation criteria for the course

  • In order to pass the course the student has to pass the exam and make at least 10% of the exercises. There will be bonus from extra exercises. To pas the exam at least half of the maximum points of the exam has to be reached. Lecture notes and exercises are enough to good grade in exam.

  • Used assessment scale is numeric (1-5)

    • Study material
    Type Name Auhor ISBN URL Edition, availability... Exam material Language
    Book "Pattern Classification" Duda RO, Hart PE, Stork DG     2nd edition, Wiley, 2001 No  English 
    Summary of lectures "Introduction to Pattern Recognition" Jussi Tohka       Yes  English 

    Prerequisites
    Code Course Credits M/R
    MAT-20500 MAT-20500 Probability Calculus 3 Recommendable
    SGN-1200 SGN-1200 Signal Processing Methods 4 Recommendable
    SGN-1250 SGN-1250 Signal Processing Applications 4 Recommendable

    Prequisite relations (Sign up to TUT Intranet required)

    Remarks

    Courses SGN-2506 and SGN-2500 are mutually exclusive. Only one can be taken.

    Scaling
    Methods of instructionHours
    Lectures 48
    Exercises 30

    Other scaledHours
    Preparation for exam 25
    Exam/midterm exam 3
    Total sum 106

    Additional information related to course
    Lectures in English. Exercise groups both in English and in Finnish.

    Correspondence of content
    8001652 Introduction to Pattern Recognition

    Course homepage

    Last modified 17.08.2007
    Modified bySari Peltonen