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SGN-2606 STATISTICAL SIGNAL PROCESSING, 5 cr
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Lecturers
Adriana Vasilache, Senior Researcher, adriana.vasilache@tut.fi
Implementation rounds
Implementation 1
| Period 1 | Period 2 | Period 3 | Period 4 | Period 5 | Summer | Language of instruction | |
| Lecture | - | - | - | 2 h/week+ | 2 h/week | - | In English only |
| Exercise | - | - | - | 2 h/week+ | 2 h/week | - | In English only |
| Exam | In English only | ||||||
Objectives
After passing this course the student will understand what estimation is,
when it is needed and will also be familiar with several basic estimators and optimal filters.
Contents
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Basic concepts of estimation. | ||
| 2. | Estimation of deterministic parameters. | ||
| 3. | Estimation of random parameters. | ||
| 4. | Optimal filtering. |
Requirements for completing the course
Final examination and two homeworks.
Assessment criteria
The final grade is 30% from the homeworks and 70% from the final exam.
Study material
| Type | Name | Author | ISBN | URL, edition, availablitity... | Exam material | Language |
| Book | "Fundamentals of Statistical Signal Processing - Estimation Theory, Estimation Theory" | Kay S. M. | 0-13-042268-1 | Prentice Hall, 1993 | Yes | English |
| Lecture slides | "Statistical Signal Processing" | Yes | English |
Prerequisites
| Number | Name | Credits | M/R |
| MAT-33310 | Statistics | 3-6 | Recommendable |
| SGN-1200 | Signal Processing Methods | 4 | Recommendable |
Additional information related to prequisites
Basic tools of statistics and general knowledge of random variables are required.
Other comments
Correspondence of content
8001403 Statistical signal processing
| Last modified | 24.08.2005 |
| Modified by | Antti Niemistö |