TUT logoSGN 21006 Advanced Signal Processing (5 cr)


Lectures

Time and place:

Tuesdaysand Thursday 12:15-14:00

Lecture room K1703 (except 7.11, when it is K1702) in Konetalo Building

Lectures on 31.10; 2.11; 7.11; 9.11;14.11; 16.11; 21.11; 23.11; 28.11; 30.11; 5.12; 7.12

 

Ioan Tabus

Office: Room TF 419, Phone +358408490783, E-mail: ioan.tabus@tut.fi

 


First Lecture: 31.10.2017 in K1703


Exercises

1.     Group 1: Wednesdays12:00-13:00 TC 303 First exercise 1.11.2017

2.     Group 2: Wednesdays13:00-14:00 TC 303 First exercise 1.11.2017

3.     Group 3: Wednesdays14:00-15:00 TC 303 First exercise 1.11.2017

4.     Group 4: Wednesdays15:00-16:00 TC 303 First exercise 1.11.2017

 

Pekka Astola


Contents:

1. Deterministic and random signals

2. Optimal filter design

3. Adaptive filter design

4. Application areas of Optimal filter design and Adaptive filter design

5. Spectrum estimation

6. Nonlinear filters


Requirements:

Project and final exam.


Lectures and link to Lecturesí Blog (Summary and Matlab codes)

1.Organization and preview of the course 31.10.2017

Lecture 1.pdf

2.Random signals2.11.2017

Lecture 2.pdf

3. Optimal Wiener Filters 7.11.2017

Lecture 3.pdf

4. Gradient based adaptive filtering 9.11.2017

Lecture 4.pdf

5. Least mean squares (LMS) algorithm and variants 14.11.2017

Lecture 5.pdf

6. Linear prediction 16.11.2017

Lecture 6.pdf

7. Least Squares and Recursive Least Squares (RLS) adaptive filters 21.11.2017

Lecture 7.pdf

8. Parameter estimation for AR and MA models. Model order selection 23.11.2017

Lecture 8.pdf

9. Spectrum estimation 28.11.2017

Lecture 9.pdf

10. Spectrum estimation methods 30.11.2017

Lecture 10-11.pdf

11. Line spectrum estimation and Direction of arrival 5.12.2017

12. Review lecture 7.12.2017

Lecture 12.pdf