13D051KES - Signals Classification and Estimation
Course specification | ||||
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Course title | Signals Classification and Estimation | |||
Acronym | 13D051KES | |||
Study programme | Electrical Engineering and Computing | |||
Module | ||||
Type of study | doctoral studies | |||
Lecturer (for classes) | ||||
Lecturer/Associate (for practice) | ||||
Lecturer/Associate (for OTC) | ||||
ESPB | 9.0 | Status | elective | |
Condition | none | |||
The goal | Course objective is for students to be able to use the techniques for signals classification and estimation. They are expected to be able to design systems for real signals acquisition, to make their normalization, pre-filtration, digital processing in time or frequency domain, parameters estimation, as well as to make signal classification if the problem of multi-class space is properly defined. | |||
The outcome | Learning outcomes of the course are following: design of systems for acquisition of video, audio and other physical signals, design of systems for digital processing of these signals, signals estimation and design of appropriate classifiers. | |||
Contents | ||||
Contents of lectures | Probability concept; Distribution of random variables and vectors; Stochastic processes; Statistical decision theory; Parameters estimation; Filtering; Signals representation; Detection and signal estimation; Hypothesis testing approach; Design of parametric and non-parametric classifiers. | |||
Contents of exercises | none | |||
Literature | ||||
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Number of hours per week during the semester/trimester/year | ||||
Lectures | Exercises | OTC | Study and Research | Other classes |
6 | ||||
Methods of teaching | lectures | |||
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 | ||||
Colloquia | 0 | |||
Seminars | 30 |