• Offered by School of Engineering
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Engineering
  • Areas of interest Engineering, Electronics
  • Academic career PGRD
  • Course convener
    • Dr Prasanga Samarasinghe
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Second Semester 2022
    See Future Offerings

This course has been adjusted for remote participation in Semester 1 2021.

Digital Signal Processing (DSP) has become over the years an important tool with applications in Electrical and Mechanical Engineering fields. DSP has penetrated many domains of applications, such as digital communications, medical imaging, audio & video systems, consumer electronics, robotics, remote sensing, finance, etc.


The Discrete-Time Signal Processing paradigm is a convenient setting to analyse the basic principles of DSP. At the end of this course, the students should be able to understand these basic principles, and apply fundamental algorithms and methods to analyse and design discrete- time systems for modern DSP applications. Though the course will focus on the study of theoretical concepts, methods and algorithms, the student will be confronted with application and implementation issues, through various examples and assignments requiring personal computer work including processing of real-world signals.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Analyse and evaluate the properties of LTI systems in terms of its z-transforms.
  2. Understand the sampling theorem and perform sampling on continuous-time signals by applying advanced knowledge of the sampling theory (i.e., aliasing, quantisation errors, pre-filtering).
  3. Apply the concepts of all-pass and minimum-phase systems to analyse the LTI system and address complex design problems.
  4. Evaluate design problems related to frequency selective processing and design FIR/IIR filters.
  5. Construct systems for spectral estimation of real signals by applying advanced knowledge of Fourier techniques.
  6. Judge implementation aspects of modern DSP algorithms.
  7. Apply the relevant theoretical knowledge to design and analyse a practical discrete-time signal system, such as a radar or audio system, using Matlab platform.
  8. Investigate advanced signal processing techniques and implement complicated systems based on the course material.

Indicative Assessment

  1. Weekly Quizzes (15) [LO 1,2,3,4]
  2. Mid-term Exam (20) [LO 1,2,3]
  3. Matlab Project (25) [LO 2,4,5,6,7,8]
  4. Final Exam (40) [LO 1,2,3,4,5,6]

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Approximately 10 hours per week. The contact hours include 1 x 2 hrs lecture and 1 x 1 hr lecture, plus up to 1 x 1.5 hrs tutorial per week.

Inherent Requirements

Not applicable

Requisite and Incompatibility

Incompatible with ENGN4537

Prescribed Texts

not applicable

Fees

Tuition fees are for the academic year indicated at the top of the page.  

Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees

Student Contribution Band:
2
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
6974 25 Jul 2022 01 Aug 2022 31 Aug 2022 28 Oct 2022 In Person N/A

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