- Basic methods of signal analysis and the computation of characteristic and invariant descriptors (features)
- Processing of signals from single sensors und homogeneous or heterogeneous Sensor-Arrays
- Dimensionality reduction of high-dimensional sensor data by linear and non-linear methods, e.g. by explicit selection of features
- Methods der cluster analysis
- Methods for multi-dimensional sensor data analysis: projection and visualisation, fusion
- methods for classification of sensor data: statistical pattern recognition, artificial neural networks, Methods of rule-based and fuzzy classification
- Advanced ptimization methods for parameter- or structure optimization of sensor systems
- Relations, dependencies, and optimization potential between sensor realization, electronics, and algorithmics.
- New aspects of reliable sensor systems (self-x properties)
Sensor Signal Processing (M, 5.0 LP)
|Module Number||Module Name||CP (Effort)|
|EIT-ISE-112-M-7||Sensor Signal Processing||5.0 CP (150 h)|
|CP, Effort||5.0 CP = 150 h|
|Position of the semester||1 Sem. in WiSe|
|Level|| Master (Advanced)|
|Area of study||[EIT-ISE] Integrated Sensor Systems|
|Reference course of study||[EIT-88.C48-SG#2021] M.Sc. Automation & Control (A&C) |
|Type/SWS||Course Number||Title||Choice in |
|SL||SL is |
required for exa.
Sensor Signal Processing
|P||56 h||94 h||
Examination achievement PL1
- Form of examination: oral examination (30 Min.)
- Examination Frequency: each semester
Evaluation of grades
The grade of the module examination is also the module grade.
Competencies / intended learning achievements
After completing this module you can...
- ... explain the relevant principals and methods from the field of Computational Intelligence, in particular for the field of sensor technology.
- ... employ selected relevant methods and their configuration in a common design environment (Matlab).
- ... design, validate, and optimize complete application-specific systems.
- ... adapt and extend the achieved implementation to changing needs.
- ... explain the interdependence of system solution with available, potentially restricted implementation platforms (Sensors/Hardware).
Requirements for attendance of the module (informal)
- [EIT-ISE-105-M-2] Electrical Measurement Technique I (M, 4.0 LP)
- [EIT-ISE-106-M-5] Electrical Measurement Technique II (M, 3.0 LP)
Requirements for attendance of the module (formal)None
References to Module / Module Number [EIT-ISE-112-M-7]
|Course of Study||Section||Choice/Obligation|
|[EIT-88.781-SG#2010] M.Sc. Electrical and Computer Engineering ||[Free Elective Area] Elective Subjects||[W] Elective Module|
|[EIT-88.A20-SG#2021] M.Sc. European Master in Embedded Computing Systems (EMECS) ||[Free Elective Area] Elective Subjects||[W] Elective Module|
|[EIT-88.D55-SG#2021] M.Sc. Embedded Computing Systems (ESY) ||[Free Elective Area] Elective Subjects||[W] Elective Module|
|[EIT-AC-MSC-RCS-WP-CORE-MPOOL-7]||RCS Core Electives|
|[EIT-EIT-MSC-TW-MPOOL-7]||Technical Elective Modules Master EIT|
|[EIT-SIAK-DT-ENG-MPOOL]||SIAK Certificate "Digital Transformation" - Modules EIT "Engineering"|
|[GS-CVT-EE-2022-E-MPOOL-6]||Catalog Electives Electrical and Computer Engineering 2022|
|[GS-CVT-EE-E-MPOOL-6]||Catalog Electives Electrical and Computer Engineering|