13M054PO - Statistical Pattern Recognition
Course specification | ||||
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Course title | Statistical Pattern Recognition | |||
Acronym | 13M054PO | |||
Study programme | Electrical Engineering and Computing | |||
Module | Applied Mathematics, Audio and Video Technologies, Biomedical and Environmental Engineering, Biomedical and Nuclear Engineering, Computer Engineering and Informatics, Electronics and Digital Systems, Energy Efficiency, Information and Communication Technologies, Microwave Engineering, Nanoelectronics and Photonics, Power Systems - Networks and Systems, Power Systems - Renewable Energy Sources, Power Systems - Substations and Power Equipment, Signals and Systems, Software Engineering | |||
Type of study | master academic studies | |||
Lecturer (for classes) | ||||
Lecturer/Associate (for practice) | ||||
Lecturer/Associate (for OTC) | ||||
ESPB | 6.0 | Status | elective | |
Condition | none | |||
The goal | Objective of the course is for the students to be informed about the statistical methods for signal classification: hypothesis testing, parametric and nonparametric classification. | |||
The outcome | Learning outcomes of the course are following: students´ ability to extract and manipulate informative features, to generate or to collect high quality and informative training sets of data, to apply appropriate statistical pattern recognition technique (hypothesis testing, parametric or nonparametric classifier). | |||
Contents | ||||
Contents of lectures | Overview of random variables and vectors; Important results from linear algebra; Feature extraction and analysis; Hypothesis testing methods; Design of parametric classifiers; Design of nonparametric classifiers; Reduction dimension methods. | |||
Contents of exercises | During the course students have to solve several practical problems: extract and analyze features from real signals, apply dimension reduction techniques, design of Bayes classifier and sequential test, design of linear and quadratic classifier. | |||
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 | 3x15 hours of lectures, 1x15 hours of practical exercising with computers | |||
Knowledge score (maximum points 100) | ||||
Pre obligations | Points | Final exam | Points | |
Activites during lectures | 0 | Test paper | 70 | |
Practical lessons | 30 | Oral examination | 0 | |
Projects | ||||
Colloquia | 0 | |||
Seminars | 0 |