Signal Processing 1 (Fundamentals)

Subject ELEN30008 (2010)

Note: This is an archived Handbook entry from 2010.

Credit Points: 12.50
Level: 3 (Undergraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2010:

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: Thirty-six hours of lectures, 12 hours tutorials, 12 hours of laboratory work
Total Time Commitment: 120 hours

431-221 Fundamentals of Signals and Systems

Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: None
Core Participation Requirements: For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry.
The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website:


Assoc Prof Erik Weyer


Melbourne School of Engineering Office
Building 173, Grattan Street
The University of Melbourne
VIC 3010 Australia
General telephone enquiries
+ 61 3 8344 6703
+ 61 3 8344 6507
+ 61 3 9349 2182
+ 61 3 8344 7707
Subject Overview:

On completion of this subject students should have a good understanding of fundamental digital signal processing operations, digital filter design and frequency domain properties of discrete time signals and systems.

Topics include motivation for signal processing with examples. Revision of deterministic signals and systems. Sampling of analog signals. Frequency domain properties: Discret time Fourier transform and Discret Fourier transform and their properties, Fast Fourier transform. Application of Fourier transform in spectral analysis and filter design. Digital filter design: filter types (lowpass, highpass, stopband, all pass, notch), phase, group delay, implications of causality, design of FIR and IIR filters. Multi-rate signal processing: upsampling, downsampling, signal rate conversion. Applications of digital signal processing.


On completing this subject the student should be able to:

  • Apply fundamental mathematical tools, in particular frequency-domain techniques, in the analysis and design of signal processing systems;
  • Design, implement and test digital filters according to given specifications.
  • Use software packages such as MATLAB for analysis and design of signal processing systems
  • Use DSP based prototyping platforms and associated software development tools to implement signal processing algorithms.
  • Formally supervised written examination 3 hours 60% (end of semester);
  • project/laboratory reports 40% (four projects/labs throughout the semester).

The written examination is a hurdle requirement: in order to receive a pass mark for the subject, students must perform at a passing standard on the written examination.

Prescribed Texts: None
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:
  • Ability to apply knowledge of basic science and engineering fundamentals

  • Ability to communicate effectively, not only with engineers but also with the community at large

  • Ability to undertake problem identification, formulation and solution

  • Ability to utilise a systems approach to design and operational performance

  • Understanding of the social, cultural, global and environmental responsibilities of the professional engineer, and the need for sustainable development

  • Capacity for independent critical thought, rational inquiry and self-directed learning

  • Intellectual curiosity and creativity, including understanding of the philosophical and methodological bases of research activity

  • Openness to new ideas and unconventional critiques of received wisdom

  • Profound respect for truth and intellectual integrity, and for the ethics of scholarship

Related Course(s): Bachelor of Engineering (Computer Engineering)/Bachelor of Science
Bachelor of Engineering (Electrical Engineering)
Bachelor of Engineering (Electrical Engineering)/Bachelor of Science
Bachelor of Engineering (Electrical) and Bachelor of Arts
Bachelor of Engineering (Electrical) and Bachelor of Commerce
Bachelor of Engineering (Electrical) and Bachelor of Laws
Bachelor of Engineering (Electrical) and Bachelor of Science
Bachelor of Engineering (EngineeringManagement) Electrical
Bachelor of Engineering (IT) Electrical Engineering

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