Course Catalog 2008-2009
Basic

Basic Pori International Postgraduate Open University

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Course Catalog 2008-2009

SGN-2606 Statistical Signal Processing, 5 cr

Course´s person responsible

Heikki Huttunen

Implementations

  Lecture times and places Target group recommended to
Implementation 1


Per 4 :
Tuesday 12 - 14, TB224
Tuesday 12 - 14, TB216
Per 5 :
Tuesday 12 - 14, TB222

 
 


Requirements

Final examination, weekly exercises and an assignment.
Completion parts must belong to the same implementation

Principles and baselines related to teaching and learning

-

Objectives

After passing this course the student will understand what estimation is, and how the methods can be applied in signal processing.

Content

Content Core content Complementary knowledge Specialist knowledge
1. Basic concepts of estimation. What is an estimator and how to compare their performance. Cramer-Rao lower bound for estimator variance.     
2. Classical tools for estimation of a deterministic parameter: minimum variance unbiased estimator (MVUE), sufficient statistic, best linear unbiased estimator (BLUE), least squares estimator.     
3. Estimation of nondeterministic parameters: the Bayesian approach.     
4. Practical signal processing applications will also be considered in each section.     


Evaluation criteria for the course

The final grade comes from the final exam. The grade is incremented by one if at least 50% of weekly exercises are done.

Assessment scale:

Numerical evaluation scale (1-5) will be used on the course

Partial passing:

Completion parts must belong to the same implementation

Study material

Type Name Author ISBN URL Edition, availability, ... Examination material Language
Book   Fundamentals of Statistical Signal Processing - Estimation Theory, Estimation Theory   Kay S. M.   0-13-042268-1     Prentice Hall, 1993      English  
Lecture slides   Statistical Signal Processing   Heikki Huttunen   -     -      English  


Prerequisites

Course O/R
MAT-33310 Tilastomatematiikka Recommended  
SGN-1200 Signaalinkäsittelyn menetelmät Obligatory  

Prerequisite relations (Requires logging in to POP)

Correspondence of content

Course Corresponds course  Description 
SGN-2606 Statistical Signal Processing, 5 cr 8001403 Statistical signal processing, 3 cu  

More precise information per implementation

  Description Methods of instruction Implementation
Implementation 1   Lectures
Excercises
Practical works
   
Contact teaching: 0 %
Distance learning: 0 %
Self-directed learning: 0 %  


Last modified17.06.2008
ModifierHeikki Huttunen