CC2011 - Digital Signal Processing
| Credit points: | 03 |
| Year: | 2018 |
| Student Contribution Band: | Band 2 |
| Administered by: | College of Science and Engineering |
This subject introduces the theory and methods of acquiring and manipulating time-varying signals using a digital computer. It covers the effects of sampling and aliasing, time domain and frequency domain representations, the Fast Fourier Transform, windowing techniques, signal convolution and correlation and filtering. Students will learn how to develop digital signal processing software, and gain experience about practical signal processing applications.
Learning Outcomes
- Explain the characteristics of sampled signals and the mechanisms of their acquisition;
- Apply time and frequency domain representations to the design and analysis of sampled data systems;
- Design DSP systems by implementing common algorithms;
- Describe the principles, application and interpretation of convolution and correlation in the context of signal processing;
- Design and implement digital filter algorithms for signal conditioning problems.
| Assumed Knowledge: | An understanding of the Fourier series and the ability to apply it. Experience applying integral transforms (e.g. Laplace transform, Fourier transform) is beneficial. Matlab programming or other programming experience is highly desirable |
| Prerequisites: | MA2000 |
Availabilities | |
| Cairns, Internal, Study Period 2 | |
| Census Date 23-Aug-2018 | |
| Contact hours: |
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| Assessment: | end of semester exam (60%); assignments (20%); second assignment (20%). |
Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.