CC2011 - Digital Signal Processing
|Student Contribution Band:
||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.
- 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
- 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.
|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
||MA2000 OR ADMITTANCE INTO MASTER OF ENGINEERING (PROF)
Study Period 2
|Census Date 29-Aug-2019
||Professor Wei Xiang.
The student workload for this
credit point subject is approximately
- 26 hours on-campus > Lectures
- 13 hours on-campus > Tutorials
- 26 hours on-campus > Practicals
- assessment and self-directed study
||end of semester exam (60%); assignments (20%); second assignment (20%).
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