NG4S804 - Applied Digital Signal Processing 01 Sep 2022 - 31 Aug 2028 | Version 4
Associated Module Information
| Module Code: | NG4S804 | ||
|---|---|---|---|
| Module Title: | Applied Digital Signal Processing | ||
| Faculty: | Faculty of Computing, Engineering and Science | ||
| Faculty Group: | Information and Electronics | ||
| Faculty Sub Group: | Electronics | ||
| Module Leader: | Adam Jones | ||
| Module Team: | Ali Roula, Eurfyl Davies, Sivagunalan Sivanathan, Alexandre Oleon | ||
| First Intended Intake: | SEP 2015 | Final Year of Intake: | 2027 |
| Date Closed: | |||
| Credit Value: | 20 | Credit Level: | 7 |
| Language: | English | ||
| Percentage of Module Taught in Welsh: | 0 | ||
| Equivalent Module: | |||
| HECOS codes: | 100163 - electrical and electronic engineering | ||
| HECOS Code Weighting: | 100 | ||
Document Version Information
| Version | 4 |
|---|---|
| Valid From | 01 Sep 2022 |
| Valid To | 31 Aug 2028 |
Module Aims
To provide a comprehensive understanding of the techniques, mathematical tools, and engineering principles for the design and evaluation of complex digital signal processing algorithms.
Content Summary
1. Concepts of analogue signal processing.
2. Concepts of digital signal processing.
3. Comprehensive understanding of the analogue-digital and digital-analogue conversion processes.
6. Number representations.
7. Discrete-time signals and systems.
8. Discrete-time convolution operation.
9. Fourier Series and Fourier Transform.
10. Discrete Fourier Transform (DFT).
11. Inverse Discrete Fourier Transform (IDFT).
12. Fast Fourier Transforms (FFT).
13. Inverse Fast Fourier Transform (IFFT).
14. Laplace Transforms.
15. Z-Transforms.
16. Inverse Z-Transforms (IZT).
17. Digital filter design (FIR).
18. Digital filter design (IIR).
19. Signal processing applications.
20. Audio processing applications.
21. Image processing applications.
Learning and Teaching Methods
| Activity Type | Hours |
|---|---|
| Lecture | 16 |
| Practical classes and workshops | 16 |
| Independent Study | 86 |
| Directed Study | 42 |
| Problem / challenge based learning | 24 |
| Tutoria | 16 |
| Total Hours Selected | 200 |
Learning Outcomes
| # | Learning Outcome |
|---|---|
| LO1 | Critically evaluate and assess the effectiveness of digital signal processing (DSP) techniques in improving the performance of digital systems. |
| LO2 | Ability to select, apply and evaluate engineering techniques, scientific principles, and mathematical tools for the design of complex digital signal processing algorithms. |
Module Requisites
N/A
Assessment Criteria
| Assessment Category | Assessment Type | Description | Duration | Word Count | Weight (%) | Best of? | Pass Mark |
|---|---|---|---|---|---|---|---|
| Asynchronous Assessment | Practical Written Work 1 | Application of DSP techniques to solve specific problems | 0 | 2000 | 60 | No | 50 |
| Synchronous Onsite Assessment (Exam) | Onsite Closed Book Examination 1 | N/A | 120 | N/A | 40 | No | 50 |
Assessment Matrix
| Assessment Type | Learning Outcomes | ||
|---|---|---|---|
| LO1 | LO2 | ||
| Practical Written Work 1 | ✔ | ✔ | |
| Onsite Closed Book Examination 1 | ✔ | ✔ | |