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:
- Analyse and evaluate the properties of LTI systems in terms of z-transforms.
- Understand the sampling theorem and perform sampling on continuous-time signals by applying advanced knowledge of sampling theory (i.e. aliasing, quantisation errors, pre-filtering).
- Apply the concepts of all-pass and minimum-phase systems to analyse LTI systems and address complex design problems.
- Evaluate design problems related to frequency selective processing and design FIR/IIR filters.
- Construct systems for spectral estimation of real signals by applying advanced knowledge of Fourier techniques.
- Judge implementation aspects of modern DSP algorithms.
- Apply the relevant theoretical knowledge to design and analyse a practical discrete-time signal system, such as a radar, image, speech, audio, bio-medical or wireless system.
Work Integrated Learning
Projects
You will undertake an individual project in this course to deal with application and implementation issues, through various examples and assignments requiring personal computer work including processing of real-world signals.
Other Information
Professional Skills Mapping:
Mapping of Learning Outcomes to Assessment and Professional Competencies
Indicative Assessment
- Weekly Quizzes (15) [LO 1,2,3,4]
- Mid-term Exam (20) [LO 1,2,3]
- Matlab Project (25) [LO 2,4,5,6,7]
- Final Exam (40) [LO 1,2,3,4,5,6]
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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
Prescribed Texts
not applicable
Minors
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 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2024 | $4980 |
- International fee paying students
| Year | Fee |
|---|---|
| 2024 | $6360 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
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 |
|---|---|---|---|---|---|---|
| 8381 | 22 Jul 2024 | 29 Jul 2024 | 31 Aug 2024 | 25 Oct 2024 | In Person | N/A |
