Vak: Adaptive Filtering credits: 5

Vakcode
SEVM21AF
Naam
Adaptive Filtering
Studiejaar
2022-2023
ECTS credits
5
Taal
Engels
Coördinator
B.D. Williams
Werkvormen
  • Hoorcollege
  • Projectonderwijs
Toetsen
  • Adaptive Filtering - Opdracht

Leeruitkomsten

At the end of this module the student is able to: 

  • Model and simulate (sensor) systems using typical computer-based tools.  

  • Clean data using advanced filter techniques, including the Wiener Filter; (normalized) Least-Mean-Square adaptive filters; Recursive Least Squares Adaptive Filters; and Kalman filtering.  

  • Describe systems in the time-domain and/or frequency domain using stationary discrete-time stochastical processes and models, such as autoregressive and moving-average models. 

Inhoud

The course covers the following topics: stationary discrete-time stochastical processes and models, (normalized) Least-Mean-Square adaptive filters, Recursive Least Squares Adaptive Filters and Kalman filtering, model simulation tools, model-based reasoning. 

Opgenomen in opleiding(en)

School(s)

  • Instituut voor Engineering
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