Open University

Advanced Signal Processing, Lectures

Tampere University

Extent

5 cr

Course dates

25.10.2022- 8.12.2022

Application period

3.8.2022-3.10.2022

Fees

75,00 € (15 €/cr)

Campus

Hervanta Campus

City

Tampere

Faculty or school

Faculty of Information Technology and Communication Sciences

Language of instruction

English

Code

COMP.SGN.200

Study fields

Technology and Natural Sciences

Mode of study

Contact teaching

Study level

Advanced studies

Advanced Signal Processing, 5 cr

Code: COMP.SGN.200

Language of instruction: English

Description

Student will learn advanced signal processing methods, especially linear optimal filter design, adaptive filters, spectrum estimation, nonlinear filters and how to select proper methods for signal processing tasks at hand.
After completing the course, the student
- Is familiar with the most important advanced signal processingr generic problems: optimal design, convergence, recursiveness in time, spectrum estimation;
- Is able to start from the formulation of a problem formulation and utilize a number of typical algorithmic tools to derive the solution;
- Knows what are the most important algorithms for optimal and adaptive filters: LMS, NLMS,RLS etc.
- Acquires practice on simulating optimal and adaptive algorithms with given input data and extracting useful performance indices helpful in comparing various algorithms.
- Knows how to integrate an optimal or adaptive filter in a number of important applications: echo cancelation, noise cancellation, channel equalization etc.

Core content

1. Deterministic and random signals: review of Fourier transform, Z transform, random variables, random signals, correlation, AR,MA, ARMA
2. Optimal filter design (Wiener filter, Least squares, essentials of estimation, MLE, CramerRao)
3. Adaptive filter design (LMS, NLMS, RLS )
4. Application areas of Optimal filter design and Adaptive filter design
5. Spectrum estimation:Frequency spectrum (needed in machine function regime diagnosis, finding periodicities in time series), Direction of Arrival spectrum
6. Nonlinear filters (median and order statistics filter family)

Course dates

Common

Lecture:

25.10.2022 08:00 - 10:00
01.11.2022 08:00 - 10:00
08.11.2022 08:00 - 10:00
15.11.2022 08:00 - 10:00
22.11.2022 08:00 - 10:00
29.11.2022 08:00 - 10:00

Groups

Group 1: Group 1

27.10.2022 10:00 - 12:00
03.11.2022 10:00 - 12:00
10.11.2022 10:00 - 12:00
17.11.2022 10:00 - 12:00
24.11.2022 10:00 - 12:00
01.12.2022 10:00 - 12:00
08.12.2022 10:00 - 12:00

Group 2: Group 2

27.10.2022 08:00 - 10:00
03.11.2022 08:00 - 10:00
10.11.2022 08:00 - 10:00
17.11.2022 08:00 - 10:00
24.11.2022 08:00 - 10:00
01.12.2022 08:00 - 10:00
08.12.2022 08:00 - 10:00

Prerequisites

Teaching material

Material

Type: Book
Name: Adaptive Filter Theory
Author: Simon O. Haykin
Exam material: No
Language: English

Material

Type: Book
Name: Spectral analysis of signals
Author: Petre Stoica and Randolph Moses
Exam material: No
Language: English

Material

Type: Lecture slides
Author: Ioan Tabus
Exam material: Yes
URL: http://www.cs.tut.fi/~tabus/course/AdvSP.html
Language: English

Material

Type: Book
Name: Optimum Signal Processing
Author: S. J. Orfanidis
Exam material: No
URL: http://eceweb1.rutgers.edu/~orfanidi/osp2e/index.html
Language: English

Assessment methods

Contact information

How to apply

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