Estimation Theory
The course is not on the list Without time-table
| Code | Completion | Credits | Range |
|---|---|---|---|
| EP33EST | ZK | 3 | 2+1s |
- Lecturer:
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- Department of Cybernetics
- Synopsis:
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Theory and practice of estimating parameters for discrete-time signals embedded in noise. Develops mathematical theory in general and considers application to problems in radar, sonar, emitter location and communication systems. Emphasis is on development of optimal algorithms and assessment of their performance. Topics include: Cramer-Rao lower bound, minimum variance unbiased estimation, least squares estimation, maximum likelihood estimation, Bayesian estimation, and Wiener filtering.
- Requirements:
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Digital Signal Processing, Linear Algebra, Probability Theory.
- Syllabus of lectures:
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- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: