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01032 Signals and Linear Systems
Danish title: Signaler og lineære systemer

Type: Å, Language: DDD
Credit points: 12,5 point
Previous course: C0122 og C4901/45020
Offered by: Department of Mathematics (MAT)
No credit points with: 01030/C0130/01031/C0131/01034/C8812/36260/ C8814/45020/C4901/C0122
Prerequisite: 01010/01011 . 01012/01014
Desirable: 10021
Recommended semester: 3rd semester
Scope and form: Lectures, group work and computer lab exercises.
Examination: (13 point scale )
Remarks: The course is part of the package for electrical engineers and is offered by the Department of Mathematics and the Department of Information Technology in collaboration.
Contact person: Poul Hjorth, MAT, Building 303, Tel. +45 4525 3061
Aim: 1. To introduce participants to the theory for infinite series, the Laplace- and Z-transformation, methods for solution of linear differential- and difference equations as well as the theory of Fourier series and the Fourier transformation. Transfer functions and frequency characteristics are introduced.
2. To introduce participants to the basic concepts of discrete and analog signals as well as the principles for linear signal processing. Discrete and continuous frequency spectra for signals are treated.
3. To introduce participants to the basic principles of the analysis of simple analog and discrete electrical circuits, including the basic structure theorems for electrical networks. The course aims to present the above subjects in an integrated manner.
Contents: 3. semester (7.5 points):

- Infinite series
- Signals, generalised functions, Laplace Transforms.
- Systems of differential equations.
- Electrical circuits and mechanical systems; stability; structure theorems; frequency characteristics; block diagrams.
- Introduction to Fourier Analysis.
- Computer lab exercises.

4. semester ( 5 points)
- Power series and Z transforms.
- Difference equations.
- Linear systems in discrete and continuous time; stability; frequency characteristics.
- Fourier transforms in discrete and continuous time.
- Sampling theorems.
- Filters.
- Computer lab exercises.