SOW-MKI54
MatLab Skills
Course infoSchedule
Course moduleSOW-MKI54
Credits (ECTS)3
Category-
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Artificial Intelligence;
Lecturer(s)
Lecturer
dr. ing. L.P.J. Selen
Other course modules lecturer
Contactperson for the course
dr. ing. L.P.J. Selen
Other course modules lecturer
Academic year2016
Period
SEM1  (29/08/2016 to 29/01/2017)
Starting block
SEM1
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesYes
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
1. After this course students will know the basic syntax for Matlab.
2. They will be able to write their own analysis scripts in Matlab.
3. They understand that Matlab was developed for matrix calculations and are able to code accordingly.
Content

During this course you will learn basic Matlab skills. The focus will be on brain imaging data, but the techniques are also applicable in other domains. Students will develop practical Matlab skills to analyze and visualize various types of signals.

Topics that will be covered: basic matrix algebra, basic programming concepts (e.g. functions, loops, logical operators), signals in the time domain, signals in the frequency domain (Fourier transformation), Linear Time Invariant Systems, multiple linear regression, convolution. This will all culminate in a frequency analysis of an MEG signal, resulting in a Time Frequency Representation, and the analysis, including contrasts, of a full brain fMRI dataset.

Literature
Syllabus ‘Signal Processing and Matlab', available on Blackboard.

Teaching formats
There will be two introductory lectures to explain the rules for this course and to provide some background on the topics covered.
Students are supposed to hand in weekly assignments that they make in their own time - they make up 20% of the final grade.
There are 5 tutorial sessions. During these sessions, questions with regard to the assignments will be answered.Note that questions, possibly with supporting code, need to be handed in beforehand through Blackboard!

Levels
AI.MA

Test information
The exam is a programming exercise that needs to be solved in 4h, this makes up for 80% of the final grade. The practical assignments make up for the remaining 20%. There will be no written exam.

Prerequisites
For this course you need basic knowledge about Linear Algebra, especially matrix multiplication, matrix inversion, solving a system of linear equations. Also some basic programming knowledge is needed (‘for', ‘while', program structure diagrams). If you have already taken PSB3BC35E (Signal Analysis and Matlab) in the psychology program, you should not take this course.

Contact information
Dr. Luc Selen; l.selen@donders.ru.nl

Required materials
Syllabus
Syllabus ‘Signal Processing and Matlab', available on Blackboard.

Instructional modes
Assignments
Attendance MandatoryYes

General
Students are supposed to hand in weekly assignments that they make in their own time - they make up 20% of the final grade.

Lecture
Attendance MandatoryYes

General
There will be two introductory lectures to explain the rules for this course and to provide some background on the topics covered.

Tutorials
Attendance MandatoryYes

General
There are 5 tutorial sessions. During these sessions, questions with regard to the assignments will be answered.Note that questions, possibly with supporting code, need to be handed in beforehand through Blackboard!

Tests
Exam
Test weight1
OpportunitiesBlock SEM1, Block SEM1