Coding and Compression Algorithms
Duration
- One Semester or equivalent
Contact hours
- 48 Hours
On-campus unit delivery combines face-to-face and digital learning.
Prerequisites
Admission to postgraduate Engineering CourseAims and objectives
(formerly Hardware Implementation of Coding and Compression Algorithms)
This unit of study aims to examine issues relating to the measure of information, relationship between information, channel capacity and applied coding techniques for improvement of information efficiency.
Unit Learning Outcomes (ULO)
Students who successfully complete this unit will be able to:
1. Appreciate the concepts of entropy, mutual information, channel capacity (K2, K3, S1, S2)
2. Execute source encoding/decoding algorithms (Huffman codes, Arithmetic codes, Lempel-Ziv coding). (K3, S1, S2, S3)
3. Design and analyse Linear block codes and Cyclic codes. (K3, S1, S2, S3)
4. Describe and use convolutional codes. (K2, K3, S1, S2).
5. Use the Viterbi Algorithm to decode convolutional Codes. (K2, K3, S1, S2).
6. Conduct experiments using simulation tools to analyse the performance coding and compression schemes and interpret results, formulate conclusions and generate high quality written reports. (K2, K3, S1, A2).
Unit Learning Outcomes (ULO)
Students who successfully complete this unit will be able to:
1. Appreciate the concepts of entropy, mutual information, channel capacity (K2, K3, S1, S2)
2. Execute source encoding/decoding algorithms (Huffman codes, Arithmetic codes, Lempel-Ziv coding). (K3, S1, S2, S3)
3. Design and analyse Linear block codes and Cyclic codes. (K3, S1, S2, S3)
4. Describe and use convolutional codes. (K2, K3, S1, S2).
5. Use the Viterbi Algorithm to decode convolutional Codes. (K2, K3, S1, S2).
6. Conduct experiments using simulation tools to analyse the performance coding and compression schemes and interpret results, formulate conclusions and generate high quality written reports. (K2, K3, S1, A2).
Unit information in detail
- Teaching methods, assessment, general skills outcomes and content.
Teaching methods
*Scheduled face to face: Lectures (34 hours), Tutorials (8 hours), Laboratory (6 hours)
*Scheduled synchronous online learning events (N/A)
Non-scheduled online learning events and activities (N/A)
Other non-scheduled learning events and activities including independent study (approx. 102 hours)
*Scheduled synchronous online learning events (N/A)
Non-scheduled online learning events and activities (N/A)
Other non-scheduled learning events and activities including independent study (approx. 102 hours)
Assessment
| Types | Individual or Group task | Weighting | Assesses attainment of these ULOs |
| Examination | Individual | 50-60% | 1,2,3,4,5 |
| Quiz(s) | Individual | 5-15% | 1,2,3 |
| Laboratory Reports | Group | 10-20% | 1,4,6 |
| Laboratory Assignment | Individual | 10-20% | 3,6 |
Minimum requirements to pass this Unit
As the minimum requirements of assessment to pass a unit and meet all Unit Learning Outcomes to a minimum standard, a student must achieve:
(i) an aggregate mark of 50% or more, and
(ii) obtain at least 40% in the final exam
Students who do not successfully achieve hurdle requirement (ii) will receive a maximum of 44% as the total mark for the unit and will not be eligible for a conceded pass.
General skills outcomes
During this unit students will receive feedback on the following key generic skills:
• Analysis skills
• Problem solving skills
• Communication skills
• Ability to tackle unfamiliar problems
• Ability to work independently
• Analysis skills
• Problem solving skills
• Communication skills
• Ability to tackle unfamiliar problems
• Ability to work independently
Content
• Digital communication systems, discrete sources and entropy, channel and channel capacity.
• Shannon's coding theorems.
• Linear block error-correcting codes.
• Cyclic codes.
• Convolutional codes.
• The Viterbi Algorithm
• Shannon's coding theorems.
• Linear block error-correcting codes.
• Cyclic codes.
• Convolutional codes.
• The Viterbi Algorithm