Course Title: Signals and Systems 1

Part A: Course Overview

Course Title: Signals and Systems 1

Credit Points: 12.00


Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

EEET2369

City Campus

Undergraduate

125H Electrical & Computer Engineering

Face-to-Face

Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016

EEET2369

City Campus

Undergraduate

172H School of Engineering

Face-to-Face

Sem 1 2017

EEET2469

Voc Training Ctre of Hong Kong

Undergraduate

125H Electrical & Computer Engineering

Face-to-Face

Offsh3 15,
Offsh3 16

EEET2486

RMIT University Vietnam

Undergraduate

125H Electrical & Computer Engineering

Face-to-Face

Viet1 2016

EEET2486

RMIT University Vietnam

Undergraduate

172H School of Engineering

Face-to-Face

Viet1 2017

Course Coordinator: Dr Katrina Neville

Course Coordinator Phone: +61 3 9925 2530

Course Coordinator Email: katrina.neville@rmit.edu.au

Course Coordinator Location: 10.07.08

Course Coordinator Availability: Email for appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

Pre-requisite (required prior study): You must have successfully completed EEET2248 - Electrical Engineering Analysis, or an equivalent course, or provide evidence of equivalent capabilities.

This course assumes that you have:

  • The ability to solve basic algebraic equations and sets of linear equations.
  • Competence in basic integral and differential calculus and differential equations.
  • Competence in the use of MATLAB for basic programming.

 


Course Description

The focus of this course is to introduce you to the fundamental concepts and techniques used in both analogue and digital signal processing (ASP and DSP) which are areas of interest if you are studying any program relating to electronic, communication and/or computer engineering.

Initially you will be introduced to the basic concept of signals and systems and learn about important mathematical techniques commonly used in the analysis of these (this includes both time- and frequency-domain analysis techniques).

You will then examine signal processing systems to determine how these can be classified as causal, stable and linear, time-invariant (LTI).

This will then allow you to utilise time and frequency domain techniques to analyse the behaviour of systems from their transfer functions, impulse responses, frequency responses and z-transforms (for discrete-time systems).

This course will also introduce you to the methods used to convert continuous-time signals to discrete-time (and vice-versa) and how to assess appropriate criteria to use to prevent signal distortion.

 


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes:

1.1 Comprehensive, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the engineering discipline.

1.2 Conceptual understanding of the, mathematics, numerical analysis, statistics, and computer and information sciences which underpin the engineering discipline.

1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.

2.1 Application of established engineering methods to complex engineering problem solving.

2.2 Fluent application of engineering techniques, tools and resources.

2.3 Application of systematic engineering synthesis and design processes.

3.2 Effective oral and written communication in professional and lay domains.

 


On completion of this course you should be able to:

  1. Apply time and frequency domain analysis techniques to different signals and systems.
  2. Classify signals and systems as discrete/continuous, linear/non-linear, causal/non-causal, time-variant/invariant, etc.
  3. Select and utilise appropriate methods for basic signal processing applications.
  4. Design and implement software simulations of common systems in MATLAB.

 


Overview of Learning Activities

Student Learning occurs through the following experiences and evaluation processes:

Theoretical concepts and mathematical methods used in the signal processing field will be introduced in weekly lectures.

Weekly lectorials will cover the practical implementation issues stemming from the lecture material and will allow you to practice your software simulation design skills.

Weekly tutorials will work through problems relating to the concepts introduced in the lectures, and

Laboratories will allow you work in groups to develop MATLAB simulations of various signals and systems.

Weekly Blackboard quizzes will also be made available to you to allow you to revise the course material and give you feedback on your progress.

 


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through our online systems.

Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.

Access to the MATLAB software package will be provided through RMIT computer labs, myDesktop and the MathWorks Total Academic Headcount student license.

 


Overview of Assessment

☒This course has no hurdle requirements.

The assessments in this course are designed for you to:

  • Research and apply techniques discussed in lectures to help evaluate your comprehension and understanding of course concepts
  • Prepare reports to evaluate your capacity to communicate your comprehension and understanding of the concepts covered in this course

Assessment types may include laboratory reports, assignments and examinations.

Assessment tasks

Assessment Task 1: Laboratory reports

Weighting 30%

This assessment task supports CLOs 1, 3 & 4

Assessment Task 2: Major assignment

Weighting 10%

This assessment supports CLOs 1, 2, 3, & 4

Assessment Task 3: Homework problems

Weighting 10%

This assessment supports CLOs 1, 2, 3 & 4

Assessment Task 4: Final exam

Weighting 50%

This assessment task supports CLOs 1, 2