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:
On successfully completing this course, students will be able to:- Analyse and evaluate the properties of LTI systems in terms of its z-transforms.
- 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).
- Apply the concepts of all-pass and minimum-phase systems to analyse the LTI system 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 or audio system, using Matlab platform.
- Investigate advanced signal processing techniques and implement complicated systems based on the course material.
Professional Skills Mapping
Mapping of Learning Outcomes to Assessment and Professional Competencies
Indicative Assessment
- Weekly Problems: 15%,
- Mid-term Quiz: 15%,
- Matlab project: 25 %,
- Final Exam: 45 %
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Requisite and Incompatibility
Prescribed Texts
- A. V. Oppenheim & R. W. Schafer, Discrete-Time Signal Processing", New International Edition (3e), Pearson, 2013.
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 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2019 | $4320 |
- International fee paying students
| Year | Fee |
|---|---|
| 2019 | $5700 |
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.
First Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 2967 | 25 Feb 2019 | 04 Mar 2019 | 31 Mar 2019 | 31 May 2019 | In Person | N/A |
