    Course module   SOWBKI316  Category     Language of instruction   English  Offered by   Radboud University; Faculty of Social Sciences; Artificial Intelligence;  Lecturer(s)     Academic year   2018   Period   SEM1  (03/09/2018 to 03/02/2019) 
 Starting block   SEM1  
 Course mode   fulltime  
 Remarks     Registration using OSIRIS   Yes  Course open to students from other faculties   No  Preregistration   No  Waiting list   No  Placement procedure    
     
Upon completion of the course, students will be familiar with the use of complex numbers and techniques from probability theory, as well as with applications of these in information theory, data compression, and signal analysis.

 During the Mathematics 2 course students will learn about:
 The concepts of entropy, information and uncertainty
 Markov chains and how they can be used to analyse certain processes
 Signals
 The properties of periodic signals
 Using complex numbers
 How signals can be seen in the time and frequency domain
 A number of signal analysis methods, especially Fourier analysis
 How filters can be used to locate signals between noise and artefacts




There will be one written exam at the end of the course. During the course there will be homework assignments that will count for 20% of the final grade. 
Mathematics 1 for AI (SOWBKI104) or any course with comparable content and Linear Algebra (SOWBKI124). 
Dr. S.A. Terwijn; E: s.terwijn@math.ru.nl; T: 024365 2073 
   Required materialsLearning Management System (Brigthspace)Don, Henk and Slagter, Luud. Lecture Notes, Available via Brightspace. 


Instructional modesHomework assignments
 Lecture
 Tutorials GeneralStudents will be supervised while they work on their homework.

 TestsExamTest weight   1 
Test type   Exam 
Opportunities   Block SEM1, Block SEM2 


  
 
 