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Undergraduate course

Signal and System Analysis

  • ECTS credits10
  • Teaching semesterAutumn
  • Course codePHYS116
  • Number of semesters1
  • LanguageNorwegian
  • Resources

Objectives and Content

Objectives:

The subject is intended as an introduction to digital signal processing and the theory that form the basis of this. Since these principles that are widely used at today¿s physics experiments, it will give a useful understanding on how data is represented and processed in these. In addition, it is useful for students who are considering applying for the Masterprograms in for instance Microelectronics or Instrumentation.

Content:

The subject explains about discrete time systems and analyses their properties in the time domain with difference equations, the frequency domain using Fourier transforms and the z-domain using Z-transforms. Specifically, some simple filters, for instance low-pass filters and band-pass filters are analysed. These are implemented as either FIR type of filters or IIR type of filters where the stability criteria are essential.

Instructive lab exercises using the simulation program Matlab enables the implementation of different digital algorithms showing practical use of the subject on e.g. music and speech. It is an advantage to have some experience in programming, but it is possible to attend to the course and learn simple Matlab programming as the course advances.

Learning Outcomes

On completion of the course

the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student

  • Is able to explain how all kinds of analog signals are represented mathematically and how the digital representation is
  • Knows what a time-discreet system is and is able to analyse this in the time-domain, the frequency domain and the z-domain.
  • Can explain different implementations of digital filters like FIR filter, IIR filters and its differences

Skills

The student

  • Can analyse various kinds of filters (lowpass, bandpass, highpass), FIR filters (feed forward only), IIR filters (includes feedback) and general stability criterion.
  • Can implement various digital algorithms in the simulation tool Matlab.

General competence

The student

  • Have knowledge that is useful for other disciplines within natural science
  • Have exercise in a systematic workflow and able to analyse complex problems using relevant tools for the discipline.

 

Grading Scale

The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.

Contact

Contact Information

advice@ift.uib.no

Exam information

  • Type of assessment: Oral examination

    Withdrawal deadline
    01.05.2018