Courses persons responsible
Ioan Tabus

Lecturers
Ioan Tabus

Implementations

	Period 1	Period 2	Period 3	Period 4	Period 5	Summer
Lecture	-	4 h/week	-	-	-	-
Exercise	-	2 h/week	-	-	-	-
Assignment	-	20 h/per	-	-	-	-
Exam

(Timetable for academic year 2006-2007)

Objectives
Student will learn basic adaptive signal processing methods, especially linear adaptive filters and learning of supervised neural networks.

Requirements for completing the course
Assignment and final exam.

Evaluation criteria for the course

Study material

Type	Name	Auhor	ISBN	URL	Edition, availability...	Exam material	Language
Book	"Adaptive Filter Theory"	S. Haykin			Prentice-Hall, 2002.	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

This course and SGN-2106 Multirate Signal Processing are lectured alternately every other year.

Distance learning

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

Scaling

Methods of instruction	Hours
Lectures	60
Exercises	24
Assignments	20

Study materials

Scaling of methods of instruction icludes the use of following study material:

literature

Other scaled	Hours
Preparation for exam	24
Exam/midterm exam	3
Total sum	131

Correspondence of content
8001253 Adaptive Signal Processing

Course homepage

Last modified	02.02.2006
Modified by	Antti Niemistö