Course Catalog 2010-2011
International

Basic Pori International Postgraduate Open University

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Course Catalog 2010-2011

SGN-1656 Signal Processing Laboratory, 5 cr

Person responsible

Mikko Parviainen

Lessons

Study type P1 P2 P3 P4 Summer Implementations Lecture times and places
Lectures
 1 h/per

 

 

 

 
SGN-1656 2010-01  

Requirements

Four laboratory exercises and their reporting.
Completion parts must belong to the same implementation

Principles and baselines related to teaching and learning

-

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 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). 

Evaluation criteria for the course

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

Prerequisites

Course Mandatory/Advisable Description
SGN-2016 Digital Linear Filtering I Advisable    
SGN-2506 Introduction to Pattern Recognition Advisable    
SGN-3016 Digital Image Processing I Advisable    
SGN-4010 Speech Processing Methods Advisable    

Prerequisite relations (Requires logging in to POP)



Correspondence of content

Course Corresponds course  Description 
SGN-1656 Signal Processing Laboratory, 5 cr 8006153 Signal Processing Laboratory, 3 cu  

More precise information per implementation

Implementation Description Methods of instruction Implementation
SGN-1656 2010-01        

Last modified01.02.2010