11194 - Signal Processing and Optimization Methods in Data Mining Modulübersicht
Module Number: | 11194 - module is no longer offered from WS 2020/21 |
Module Title: | Signal Processing and Optimization Methods in Data Mining |
Signalverarbeitung und Optimierungsmethoden für Data Mining | |
Department: | Faculty 3 - Mechanical Engineering, Electrical and Energy Systems |
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Language of Teaching / Examination: | English |
Duration: | 1 semester |
Frequency of Offer: | Every winter semester |
Credits: | 6 |
Learning Outcome: | Students will get detailed knowledge about signal processing issues and notions of optimization methods, with practical examples and exercises. In the optimization part students will learn foundations of optimization methods and their numerical application in engineering. They will be skilled to optimize various types of practical industrial problems. |
Contents: | The first part of the course introduces foundations of signal processing methods in electrical power engineering. Introducing lectures provide ideas of discrete representations of continuous signal with basic functions and signal orthogonal projection. Next stage of the course concerns continuous representations of deterministic signals. Introduced definitions allow passing into nonparametric time-frequency representations. Then, follow the time-scale representations with wavelets. Backgrounds of statistical signal processing are introduced with outlined parameter estimation, optimal filtering, linear modeling and estimation. Finally, various methods of parametric spectrum estimation are outlined. Examples of application in electrical engineering are presented throughout the course. |
Recommended Prerequisites: | Courses on Algebra and Analysis |
Mandatory Prerequisites: | None |
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Module Examination: | Final Module Examination (MAP) |
Assessment Mode for Module Examination: |
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Evaluation of Module Examination: | Performance Verification – graded |
Limited Number of Participants: | None |
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Remarks: | The lecture will be not offered in winter semester 2017/18. |
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Phase-out module since: 04.10.2017
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