Course Catalog 2006-2007

SGN-2016 DIGITAL LINEAR FILTERING I, 5 cr
Digital Linear Filtering I

Courses persons responsible
Tapio Saramäki

Lecturers
Tapio Saramäki

Lecturetimes and places
Per II: Monday 12 - 14, TB215
Per II: Wednesday 12 - 14, TB215

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

Objectives
Basics and needs for linear digital filtering. Filter structures as well as various responses characterizing the performance of linear digital filter. Conventional design techniques and finite wordlength effects.

Content
Content Core content Complementary knowledge Specialist knowledge
1. What is a digital filter and how to analyse its performance with the aid of various responses? Various structures for implementing digital filters.  Introductory filtering examples and the effect of poles and zeros for various responses of digital filters.  During the lectures, some extra indormation not included in the lecture notes is given. 
2. Design and implementation of conventional finite-impulse response (FIR)digital filters. The main emphasis is laid on synthesizing linear-phase FIR filters.  The lecture notes review various structures for implementing digital filters in order to make the terminology familiar.    
3. Design and implementation of classical infinite-impulse response digital filters.       
4. Finite wordlegth effects when implementing digital filters using the fixed-point arithmetic.       

Requirements for completing the course
Final examination.

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. Course acceptance threshold is approximately half the maximum exam points.

  • Used assessment scale is numeric (1-5)

  • Study material
    Type Name Auhor ISBN URL Edition, availability... Exam material Language
    Summary of lectures "Digital Linear Filtering 1" Tapio Saramäki       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.

    Remarks

    Courses SGN-2016 and SGN-2010 are mutually exclusive. Only one can be taken.

    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: 45 %
    - Distance learning: 0 %
    - Proportion of a student's independent study: 55 %

    Scaling
    Methods of instructionHours
    Lectures 75
    Exercises 30

    Other scaledHours
    Preparation for exam 20
    Exam/midterm exam 3
    Total sum 128

    Correspondence of content
    8001063 Digital linear Filtering I

    Course homepage

    Last modified 02.02.2006
    Modified byAntti Niemistö