Course Catalog 2013-2014
Basic

Basic Pori International Postgraduate Open University

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Course Catalog 2013-2014

SGN-90006 Signal Processing Doctoral Seminar, 2-8 cr

Additional information

Suitable for postgraduate studies

Person responsible

Ioan Tabus, Ari Visa, Karen Eguiazarian, Ulla Ruotsalainen

Lessons

Study type P1 P2 P3 P4 Summer Implementations Lecture times and places
Seminar
 2 h/week
+2 h/week

 

 

 
SGN-90006 2013-01 Wednesday 10 - 12, TC133
Wednesday 10 - 12, TC219
Wednesday 10 - 12, TB220
Wednesday 10 - 12, TB215
Wednesday 10 - 12, TB214

Learning Outcomes

- Is familiar with a specialized area of signal processing where there is active research worldwide - Is able to critically evaluate the content of a specialized textbook in signal processing area - Acquires practice skills in preparing a presentation directed to a specialist audience - Acquires practice skills in defending his views when subject to criticism from the audience - Acquires practice skills in asking questions during the presentations of scientific topics

Content

Content Core content Complementary knowledge Specialist knowledge
1. Seminar topics: signal processing and related topics, with emphasis on algorithms.     

Prerequisite relations (Requires logging in to POP)



Correspondence of content

Course Corresponds course  Description 
SGN-90006 Signal Processing Doctoral Seminar, 2-8 cr SGN-9106 Signal Processing Graduate Seminar I, 3 cr +
SGN-9206 Signal Processing Graduate Seminar II, 3-8 cr +
SGN-9306 Signal Processing Graduate Seminar III, 3-8 cr +
SGN-9406 Signal Processing Graduate Seminar IV, 3-8 cr
 

More precise information per implementation

Implementation Description Methods of instruction Implementation
SGN-90006 2013-01 SGN-90006 Signal processing doctoral seminar, 3cr 3rd period, Wednesdays 10-12 at TB220 (TB215 on 15.1.2014 and TB214 on 5.2.2014 exceptionally) First meeting 8.1.2014 Instructors: Olli Yli-Harja Instructor reception on wednesdays 14-16 at TE306 Requirements: One student presentation and participation in lectures and presentations Registration: By email to yliharja@cs.tut.fi or at the first lecture Challenges in computational modeling and machine learning The focus of the seminar is to explore limitations of machine learning, basic assumptions on which mathematical modeling is based on, and principled limitations of computational approaches in science. The seminar is composed of a series of invited lectures ranging from statistical inference, machine learning to the pragmatistic approach to the philosophy of science, and student presentations on selected topics. Individual guidance sessions with the instructor are available for students to help the preparation of their presentations. The seminar concentrates on principled properties and limitations of computational approaches instead of details of algorithmic methods. The aim is to reveal useful viewpoints that are applicable in practical engineering work, e.g. related to "big data". We study success cases in machine learning as well as approaches which run into unavoidable difficulties.        

Last modified04.02.2013