Digital Signal Processing
Duration
- One Semester or equivalent
Contact hours
- 60 Hours
On-campus unit delivery combines face-to-face and digital learning.
2022 teaching periods
Hawthorn
| Higher Ed. Semester 2 | ||
|---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
Aims and objectives
This unit of study aims to introduce the principles of signal processing, with emphasis on discrete signal processing. It will provide the students with the theoretical basis for understanding digital signal processing fundamentals schemes along with discussions concerning the basis of statistics, probability and stochastic processes.
Unit Learning Outcomes (ULO)
Students who successfully complete this unit will be able to:
1. Appreciate time domain and frequency domain representations and properties of signals and signal processing systems (K1, K2, S1).
2. Appreciate fundamentals of stochastic signals and stochastic signal processing. (K1, K2, S1)
3. Analyse sampling and digital quantification mechanisms in digital signal processing. (K1, K2, S1)
4. Apply transformation methods to the analysis of continuous and discrete signals and the analysis and design of digital filters in the time and frequency domains. (K1, K2, K3, S1, S2)
5. Apply software tools to the design and analysis of signal processing systems. (K1, K2, S1, S2)
Unit information in detail
- Teaching methods, assessment, general skills outcomes and content.
Teaching methods
Assessment
| Types | Individual or Group task | Weighting | Assesses attainment of these ULOs |
| Test | Individual | 10% | 1,3,4 |
| Practical work | Individual/Group | 40% | 4,5 |
| Examination | Individual | 50% | 1,2,3,4 |
General skills outcomes
You will be provided with feedback on your progress in attaining the following generic skills:
| K1 | Basic Science: Proficiently applies concepts, theories and techniques of the relevant natural and physical sciences. |
| K2 | Maths and IT as Tools: Proficiently uses relevant mathematics and computer and information science concepts as tools. |
| K3 | Discipline Specific: Proficiently applies advanced technical knowledge of the specific discipline within that context. |
| S1 | Engineering Methods: Applies engineering methods in practical applications. |
| S2 | Problem Solving: Systematically uses engineering methods in solving complex problems. |
| S3 | Design: Systematically uses engineering methods in design. |
| A2 | Communication: Demonstrates effective communication to professional and wider audiences. |
Content
· Statistics, Applied Probability and Noise
· Review of continuous time signals, spectra and systems
· Discrete Time Signals
· Discrete systems
· Design of Digital Filters
Study resources
- Recommended reading and references.
Recommended reading
· Ambardar, A. (1999). Analog and Digital Signal Processing (2nd Ed). Brooks/Cole.
· Gonzales, RC. & Woods, R.E. (2007). Digital Image Processing. 3rd Ed Pearson/Prentice Hall.
· Oppenheim, AV & Schafer, RW. (2010). Discrete-time Signal Processing.3rd Ed Prentice-Hall.
References
Course notes including lecture, tutorial and laboratory material are available on-line in the Blackboard site for this subject.