|Semester 1, 2022 Toowoomba On-campus|
|Faculty or Section :||Faculty of Health, Engineering and Sciences|
|School or Department :||School of Engineering|
|Student contribution band :||Band 2|
|Grading basis :||Graded|
|Version produced :||2 July 2022|
Examiner: John Leis
Pre-requisite: ELE1301 or Students must be enrolled in one of the following Programs: GCEN or METC or GCNS or GDNS or MENS or MEPR
Advanced digital encoding, compression and encryption are vital to modern telecommunications and networks. Engineers operating at the advanced level of telecommunications networks are required to understand, maintain and configure advanced telecommunications systems. Furthermore, they may be required to design new systems involving data compression and encryption.
This course examines the methods used for coding, transmitting and storing continuous signals such as speech, music, images and video. The course covers such topics as data compression, encryption, and error control in a digital transmission system.
The course also seeks to impart an understanding of current research problems in the digital communications field. It is thus suitable for students who may wish to undertake research and development work in this important field.
Course learning outcomes
The course objectives define the student learning outcomes for a course. On completion of this course, students should be able to:
- describe quantization techniques;
- to explain the operation of lossless coding algorithms, and in particular their relationship to data probabilities;
- implement transform-domain encoders and decoders;
- describe coding algorithms used in speech communications such as linear predictive coding and code-excited linear prediction;
- describe coding algorithms used in video communications such as the discrete cosine transform and intraframe predictors;
- analyse the computational complexity of coding algorithms and assess their suitability for real-time implementation on DSP systems;
|1.||Principles of quantization||20.00|
|3.||Audio signal modelling||20.00|
|4.||Video signal modelling||20.00|
|5.||Lossless coding algorithms||10.00|
|6.||DSP systems implementation||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.
|Weighting (%)||Course learning outcomes|
|Time limited online examinatn||No||50||1,2,3,4,5,6|