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| Detailed information |
| Original study plan |
Master's programme Electronics and Information Technology 2025W |
| Learning Outcomes |
Competences |
| Students know and understand advanced signal processing algorithms. They understand how to efficiently implement them in digital hardware. They have a deep understanding of potential implementation issues and know how to optimize algorithms to ensure efficient implementation.
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| Skills |
Knowledge |
- Ability to implement efficient algorithms for solving least squares problems and systems of equations (k1,k2,k3)
- Ability to implement efficient methods for solving sparse estimation and reconstruction problems (k1,k2,k3)
- Ability to implement adaptive filters (k1,k2,k3)
- Knowledge of implementation aspects of selected machine learning and data science algorithms in digital hardware (k1,k2)
- Design of efficient hardware architectures (memory management, arithmetic simplifications, approximation of operations, etc.) (k1,k2,k3,k6)
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- Kaczmarz Algorithmen, Cyclic Coordinate Descent Algorithmen
- Linearized Bregman-based Sparse Kaczmarz, Sparse Cyclic Coordinate Descent
- LMS, Sparse LMS
- FFT architectures
- Tree-based machine learning methods and architectures thereof
- Sparse Frequency Estimation
- Time/Frequency Estimation
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| Criteria for evaluation |
Oral or written exam (75%), grading of homework (25%)
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| Methods |
Lecture, Matlab/VHDL/bit-true demos, solving of selected homework examples, video recording of lecture (screen capture and audio recording)
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| Language |
Upon agreement with participants – English or German |
| Study material |
- Lecture slides
- U. Meyer-Baese, Digital Signal Processing with Field Programmable Gate Arrays, *E. Chong, S. Zak, An Introduction to Optimization, Wiley, 2001.
- J. H. Friedman, R. Tibshirani und T. Hastie, The Elements of Statistical Learning, Springer, 2001.
- U. Spagnolini, Statistical Signal Processing in Engineering, Wiley 2018.
- H. Bauschke et. al, Fixed-Point Algorithms for Inverse Problems in Science and Engineering, Springer, 2011.
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| Changing subject? |
No |
| Earlier variants |
They also cover the requirements of the curriculum (from - to)
489WSIVESPK19: KV Efficient Signal Processing Algorithms (2019W-2022S)
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