1. Handbook
  2. Subjects
  3. Signal Processing

Signal Processing (ELEN90058)

Graduate courseworkPoints: 12.5On Campus (Parkville)

You’re viewing the 2026 Handbook:
Or view archived Handbooks

Overview

Availability
Semester 2 - On Campus
FeesLook up fees

AIMS

This subject provides an introduction to the fundamental theory of time domain and frequency domain representation of discrete time signals and linear time invariant dynamical systems, and how this theory is used to analyse and design digital signal processing systems and algorithms. Topics include:

  • Applications of signal processing techniques;
  • Sampling of analog signals, anti-aliasing filters;
  • Frequency-domain analysis of signals and systems, Discrete Time Fourier Transform, Discrete Fourier Transform, Fast Fourier Transform;
  • Digital filters, low-pass, high-pass, band-pass, stop-band and all pass filters. Phase and group delay, FIR and IIR filters;
  • Design of digital FIR and IIR filters;
  • Multi-rate signal processing, with a focus on up-sampling, down-sampling, and sampling rate conversion;
  • Simple non-parametric methods for spectral estimation.

This fundamental material will be complemented by exposure to MATLAB tools for signal analysis and a DSP (Digital Signal Processor) based development platform for the implementation of signal processing algorithms in the laboratory.

INDICATIVE CONTENT

Sampling of continuous time signals, Design of anti-aliasing filters, Time and frequency representation of discrete time signals and discrete time linear time invariant systems, Discrete Time Fourier Transform and z-transform and their properties, Low order lowpass, highpass, bandpass, bandstop filters, All-pass filter, Design of IIR filters using the bilinear transformation, Design of FIR filters with linear phase using windowing techniques and the Parks McClelland method, Discrete Time Fourier transform and its properties, Fast Fourier Transform, The use of the DFT in implementation of linear filtering algorithms, Up-sampling and down-sampling, multistage and computationally efficient implementations of up-samplers and down-samplers, Energy and power spectra for deterministic signals.

Intended learning outcomes

INTENDED LEARNING OUTCOMES (ILOs)

 

Having completed this unit 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 simple digital filters according to given specifications
  • Use software such as MATLAB for the analysis and design of signal processing systems
  • Use DSP based prototyping platforms and associated software development tools to implement signal-processing algorithms

Generic skills

On completion of this subject, students will have developed the following skills:

  • ability to identify, analyse, and develop innovative solutions to complex and open-ended problems, considering various constraints and requirements. 
  • capacity for independent critical thought, rational assessment and self-directed learning; 
  • ability to communicate and work effectively with teams; 
  • capability to clearly articulate technical information, ideas, and solutions to both technical and non-technical audiences, through oral presentations, written reports, and other media. 
  • ability to articulate and uphold ethical standards and professional responsibilities, including honesty, accountability, and respect for others. 
  • ability to lead teams, motivate colleagues, and make strategic decisions, while also demonstrating initiative and accountability in individual roles. 

Last updated: 10 February 2026