SGN-26006 Advanced Signal Processing Laboratory, 5 cr

Person responsible

Sari Peltonen, Kaisa Liimatainen

Lessons

Implementation Period Person responsible Requirements
SGN-26006 2016-01 1 - 4 Kaisa Liimatainen
Sari Peltonen
Four laboratory exercises reported and accepted.

Learning Outcomes

After completing the course, students are able to apply basic signal processing methods to solve problems that are closely related to practical problems. To complete the course, students are required to pass four assignments in groups of one or two students. The assignments in the course are from various areas of signal processing. During the course, students apply their background knowledge, improve their problem solving strategies and information search abilities in order to solve practical problems. Students will learn to introduce the methods they have used to conduct a given experiment, present results and conclusions of the experiment in a form of written reports and possibly other deliveries such as program code.

Content

Content Core content Complementary knowledge Specialist knowledge
1. All the individual tasks mentioned are completed successfully (i.e. every questions is given an answer).  Reasons for observed phenomena are analyzed and discussed based on given literature and background knowledge.  Improvements to tested methods are proposed and analyzed by comparison to the tested method numerically. 
2. The report and other possible deliverables fulfill the criteria set by the advisor of each assignment.  The report is formal i.e. follows the structure: introduction, material and methods, results and conclusions.  Besides the previous the layout of the report reminds scientific publications (see e.g. IEEE conference papers). 

Instructions for students on how to achieve the learning outcomes

To pass the course, it is required that four exercises have been returned and accepted.

Assessment scale:

Evaluation scale passed/failed will be used on the course

Partial passing:

Completion parts must belong to the same implementation

Study material

Type Name Author ISBN URL Additional information Examination material
Other online content     Course web page         No   
Other online content     Course web page         No   

Prerequisites

Course Mandatory/Advisable Description
SGN-21006 Advanced Signal Processing Advisable    
SGN-31007 Advanced Image Processing Advisable    
SGN-41007 Pattern Recognition and Machine Learning Advisable    



Correspondence of content

Course Corresponds course  Description 
SGN-26006 Advanced Signal Processing Laboratory, 5 cr SGN-1656 Signal Processing Laboratory, 5 cr  

Updated by: Värri Alpo, 08.04.2016