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Course Catalog 2012-2013
SGN-2407 Spectrum Estimation and Array Signal Processing, 5 cr |
Additional information
Suitable for postgraduate studies
Person responsible
Ioan Tabus
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Final exam or alternatively a project work in the area of the course.
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-1201 Signal Processing Methods | Mandatory | |
| SGN-1251 Signal Processing Applications | 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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More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |
| This is a self-study course which is focused on spectrum estimation methods and their applications. |