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Course Catalog 2010-2011
SGN-2407 Spectrum Estimation and Array Signal Processing, 5 cr |
Person responsible
Ciprian Giurcaneanu
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Final exam.
Learning outcomes
(1) Knowledge of the basic topics in spectrum estimation and array signal processing; (2) Understanding of the statistical accuracy bounds for the methods investigated; (3) Carry out routine implementations for the algorithms described in the course; (4) Be able to choose the most suitable method for estimating the spectra of measured signals. (5) Be able to use the skills acquired in this course for better understanding the content of other courses of the Department of Signal Processing. (6) In some cases, be able to propose new approaches for signal analysis and interpretation.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Periodogram and correlogram. | ||
| 2. | Non-parametric spectrum analysis. | ||
| 3. | Filter-bank approach. | ||
| 4. | Parametric methods for line spectra. | ||
| 5. | Rational spectral methods. | ||
| 6. | Spatial methods. |
Study material
| Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
| Book | Spectral analysis of signals | Petre Stoica and Randolph Moses | 0-13-113956-8 | English | |||
| Lecture slides | English |
Prerequisites
| Course | Mandatory/Advisable | Description |
| SGN-1157 Signal Processing Basics | Mandatory | |
| SGN-1201 Signaalinkäsittelyn menetelmät | Mandatory | |
| SGN-1251 Signaalinkäsittelyn sovellukset | Advisable |
Additional information about prerequisites
Either SGN-1157 or SGN-1201 is required.
Prerequisite relations (Requires logging in to POP)
Correspondence of content
| Course | Corresponds course | Description |
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Additional information
Suitable for postgraduate studies
More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |
| Teach the student about spectrum estimation methods and their applications. |