13E053SAS - Spectral Signal Analysis
| Course specification | ||||
|---|---|---|---|---|
| Course title | Spectral Signal Analysis | |||
| Acronym | 13E053SAS | |||
| Study programme | Electrical Engineering and Computing | |||
| Module | Signals and Systems | |||
| Type of study | bachelor academic studies | |||
| Lecturer (for classes) | ||||
| Lecturer/Associate (for practice) | ||||
| Lecturer/Associate (for OTC) | ||||
| ESPB | 6.0 | Status | elective | |
| Condition | Digital signal processing, Stochastic systems and estimation | |||
| The goal | Introduce students to basics methods for time-series analysis and spectral estimation. Enable students to practically implement and interpret the results of these algorithms using Matlab/Octave and Python. | |||
| The outcome | Students will understand theoretical and practical aspects of classical and parametric algorithms for estimating power spectra of wide-sense stationary stochastic signals. Students will be enabled to properly choose, practically implement and adequately tune the spectral estimation algorithms, and to interpret the results obtained by applying these methods to realistic signals. | |||
| Contents | ||||
| URL to the subject page | https://automatika.etf.bg.edu.rs/index.php/sr/spektralna-analiza-signala-os3sas | |||
| URL to lectures | https://teams.microsoft.com/l/team/19%3AGs-R9JY3pc_pzFrEVAJAhff5b2G1fy5RCgSGxn25D4c1%40thread.tacv2/conversations?groupId=87ed92c2-489d-4311-a317-fe8134bbe31b&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba | |||
| Contents of lectures | Stochastic processes. Classical methods for spectral analysis: periodogram, Blackman-Tukey method. Parametric time-series modelling: AR, MA and ARMA models, linear prediction. Spectral estimation of AR models: Yule-Walker equations, Levinson-Durbin recursion, lattice filters, autocorrelation/(modified) covariance/Burg methods. Effect of measurement noise. Model order selection. | |||
| Contents of exercises | In class, with the teachers supervision and aid, the students will implement and verify methods covered in lectures. As a homework assignment, each student will be given samples of a signal, and their assignment will be to individually estimate and analyse the spectrum of the sampled signal. | |||
| Literature | ||||
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| Number of hours per week during the semester/trimester/year | ||||
| Lectures | Exercises | OTC | Study and Research | Other classes |
| 3 | 1 | 1 | ||
| Methods of teaching | 45 hours of lectures + 15 hours of auditory exercises + 15 hours of practical exercises with computers | |||
| Knowledge score (maximum points 100) | ||||
| Pre obligations | Points | Final exam | Points | |
| Activites during lectures | 0 | Test paper | 0 | |
| Practical lessons | 0 | Oral examination | 70 | |
| Projects | 30 | |||
| Colloquia | 0 | |||
| Seminars | 0 | |||