ETEN2000/ETEN5000 – Signals and Systems
Undergraduate/postgraduate course, Curtin University, School of Electrical Engineering, Computing and Mathematical Sciences (EECMS), 2022
The course will cover continuous-time and discrete-time signals, specifically their mathematical representations, properties and classifications, such as power and energy signals. Special attention is devoted to Linear time-invariant systems, where concepts such as impulse response, convolution are developed. The course also cover the Fourier series representation of periodic signals, which leads to continuous-time Fourier transform (and discrete-time Fourier transform), Laplace transform and Sampling theorem. Students will be introduced to Matlab.
Introduction
Signals and Systems is a fundamental subject in engineering, particularly electrical engineering. This course is an introduction to the basic concepts and theory of signals and systems. The background assumed is calculus, experience in manipulating complex numbers, and some exposure to differential equations. Students will learn the concept of signals and how to analyse and characterise various types of signals. Students will also learn the concept of systems and how these can be characterised by the relationship between their input and output signals. Since Signal & Systems is one of the foundation blocks in electrical engineering, the effort invested in his unit will be well rewarded in the students’ future endeavours.
Unit Learning Outcomes
On successful completion of this unit students can:
- Classify signals and systems
- Perform basic operations on signals
- Compute the response of a linear time-invariant system
- Use transform techniques to analyse linear systems
- Carry out signals and systems simulations using Matlab
Learning Activities
Students will be exposed to concepts such as modelling and characterisation of signals and subsequently systems. The modelling and characterisation are divided into continuous-time and discrete-time parts. Students will learn new mathematical tools such as Fourier decomposition, Fourier transform, and Laplace transform to analyse and characterise signals and systems.