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Course unit, curriculum year 2020–2021
COMP.SGN.200
Advanced Signal Processing, 5 cr
Tampere University
- Description
- Completion options
Teaching periods
Active in period 2 (19.10.2020–31.12.2020)
Active in period 3 (1.1.2021–7.3.2021)
Active in period 4 (8.3.2021–31.5.2021)
Course code
COMP.SGN.200Language of instruction
EnglishAcademic year
2020–2021Level of study
Advanced studiesGrading scale
General scale, 0-5Persons responsible
Responsible teacher:
Ioan TabusResponsible organisation
Faculty of Information Technology and Communication Sciences 100 %
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)
Learning outcomes
Prerequisites
Recommended prerequisites
Further information
Learning material
Equivalences
Studies that include this course
Completion option 1
Completion of all options is required.
Participation in teaching
19.10.2020 – 04.12.2020
Active in period 2 (19.10.2020–31.12.2020)