| Semester 2, 2023 Springfield On-campus | |
| Units : | 1 |
| School or Department : | School of Engineering |
| Grading basis : | Graded |
| Course fee schedule : | /current-students/administration/fees/fee-schedules |
Staffing
Course Coordinator:
Overview
Digital signal processing is essential in many telecommunications, instrumentation, measurement, control and power applications. As such, a working knowledge of digital sampling and discrete-time processing provides an essential basis for understanding existing engineering systems, and facilitates the design of new systems for emerging applications.
Signal processing is the treatment of signals to enable detection, classification, transmission or enhancement. Such signals may, for example, be the apparent noise generated by a mechanical process, music, speech or other audio, or a video image. This course aims to give the student a thorough grounding in the theoretical and practical aspects of digital signal processing. Practical applications of signal processing are emphasised via directed experimentation and assignment work.
Course learning outcomes
The course objectives define the student learning outcomes for a course. On completion of this course, students should be able to:
- distinguish between a deterministic and a random signal;
- describe any signal probabilistically in terms of amplitude and spatial, frequency or temporal functions;
- describe a deterministic signal in terms of transforms and difference equations;
- design and implement signal processing algorithms for sampled signals such as audio;
- design and implement signal processing algorithms for sampled two-dimensional signals such as images;
- design and implement digital filter algorithms for signal conditioning problems;
- be able to implement signal processing algorithms such as Fourier transforms, convolution, correlation, and filtering.
Topics
| Description | Weighting(%) | |
|---|---|---|
| 1. | Fourier analysis | 20.00 |
| 2. | Random processes | 20.00 |
| 3. | Digital signal processing | 50.00 |
| 4. | Information theory | 10.00 |
Text and materials required to be purchased or accessed
Student workload expectations
To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.
Assessment details
| Description | Group Assessment |
Weighting (%) | Course learning outcomes |
|---|---|---|---|
| Model (theoretical) | No | 10 | 1,2,3 |
| Problem Solving | No | 40 | 4,6,7 |
| Time limited online examinatn | No | 50 | 1,2,3,4,5,6,7 |