| 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, 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). |
- Introduction to Statistical Pattern Recognition, Keinosuke Fukunaga, Academic Press, 1990 (Original title)
- Pattern Recognition, S. Theodoridis, K. Koutroumbas, Academic Press, 2009. (Original title)
- Introduction to Data Mining (2nd Edition), Pang-Ning Tan, Michael Steinbach, et. al, Pearson, 2018 (Original title)
- Statistical Pattern Recognition (3rd edition), A. Webb, K. Copsey, Wiley, 2011 (Original title)
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