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Avanceret signalbehandling og analyse (TIADSI1U01) (Q3) ( forår 2011 - 5 ECTS )

Rammer for udbud

  • Uddannelsessprog: engelsk
  • Niveau: Graduate course
  • Semester/kvarter: Q3
  • Timer per uge: 4
  • Deltagerbegrænsning: None
  • Undervisningssted: Århus
  • Hovedområde: Ingeniørhøjskolen
  • Udbud ID: 29792

Formål

The aim of the course is to give participants insight into methods for processing and analyzing of real world signals with a stochastic or incomplete nature. Participants will gain experience with methods for interpolation, analysis and prediction of stochastic signals based on advanced filtering techniques.  Participants will also gain familiarity with different models used for spectral analysis of stochastic signals.

Indhold

Real world signals, such as music, images or physiological signal from the human body, are stochastic in nature. Sometimes such signals are also corrupted and incomplete. The course will present different methods for interpolation, reconstruction and prediction of such signals based on advanced filtering techniques. Also methods for analysis of such signals will be presented i.e. methods for signal modeling and spectral estimation.

Faglige forudsætninger

Students most know of signal analyses and signal processing at the level of a bachelor degree in electronic engineering or software engineering. Bachelors in computer science, physics or mathematics, with primary knowledge of signal analyses and signal processing will also be able to attend the course. Primary knowledge of stochastic signal processing is required.

Underviser

Jakob Juul Larsen

Undervisnings- og arbejdsform

Lectures and labs.

Litteratur

To be announced

Eksamensterminer

March, re-examination after appointment with lecturer

Udbyder

Aarhus School of Engineering (ASE)

Tilmelding til undervisning

http://mit.au.dk/

Læringsmål

The participants must at the end of the course be able to:

  • Apply methods for reconstruction and interpolation of incomplete and corrupted real world signals, based on signal modeling and advanced filtering techniques .
  • Apply methods for prediction of real world signals, based on signal modeling and advanced filtering techniques, such as Linear Predictive Filters and Optimal Linear Filters.
  • Implement and compare parametric/non-parametric methods for power spectral estimations.
  • Explain basic wavelet methods for signal synthesis and analyses.
  • Compare models of stochastic signals and systems for proceeding and analyzing of real world signals.
  • Reason and analyze about systems that processes stochastic signals.

Bedømmelse

Written exam, 2 hours. Grades on the 7-scale. External examinor.