• Offered by Research School of Engineering
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Engineering
  • Areas of interest Engineering
  • Academic career UGRD
  • Course convener
    • Dr Pallage Abhayapala
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in First Semester 2016
    See Future Offerings

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 imple-
mentation 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.

Professional Skills Mapping:
Mapping of Learning Outcomes to Assessment and Professional Competencies 

Indicative Assessment

Weekly problems; mid-semester quiz; Matlab project; final exam.

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Workload

Lectures; Weekly tutorial; Computer laboratories.

Requisite and Incompatibility

To enrol in this course you must have completed ENGN2228.

Majors

Minors

Fees

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

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and 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). You can find your student contribution amount for each course 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
Domestic fee paying students
Year Fee
2016 $3480
International fee paying students
Year Fee
2016 $4638
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.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
3383 15 Feb 2016 26 Feb 2016 31 Mar 2016 27 May 2016 In Person N/A

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