EEE4114F: Digital Signal Processing

Course presentation

Monday, Wednesday periods 6 and 7 (CENGSEM). The official course handout is available here. A set of about 28 lectures of core DSP concepts will be presented by A/Prof. Nicolls and a second set of lectures on machine learning will be presented by Mr. Jarryd Son.

Teaching assistance

Teaching assistant: Yaaseen Martin (MRTMOG014@myuct.ac.za).

Lecture notes

Introduction (2up).
Discrete-time signals and systems (2up).
The z-transform (2up).
Sampling of continuous-time signals (2up).
The Discrete Fourier Transform (2up).
Transform analysis of LTI systems (2up).
Filter design (2up).

These notes are licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. Latex source for producing them can be downloaded here.

Example Matlab code

Zero padding for linear convolution using the FFT.
Use of windows for Spectrum estimation.
Any other code in the examples directory.

Problem Sets and Matlab Assignments

To be handled through Vula.

DSP Project

You are expected to undertake a substantial project (approximately 10-20 hours) for this course. Details will follow.

Class Tests

Details to follow. Past tests and exams can be found here.

Exam information

The exam consists of two parts, with the approximate breakdown as follows:

Core DSP: 60%
Machine learning: 40%

Nominally assignments and projects will count 20% towards the final mark, class tests will count 20%, and the remaining 60% will come from the exam. However, these proportions may be adjusted to give you the maximum benefit. You will be given this information sheet in the exam.

Resources

Some web links.
Past tests and exams for the course.

Last modified: Fri Feb 7 12:46:44 SAST 2020