Signal Processing & Machine Learning

The Signal Processing Division (also fondly referred to as the DSP Division thanks to its penchant for solving problems digitally) works in a variety of areas that involve the manipulation of information-bearing signals. The division comprises both those people who specialise in the transmission of such signals over large distances (Telecommunications) and through complex networks (Network Theory), and those people who are interested in extracting and embedding the information in the signal – whether it be digital data (Digital Communications and Media) or natural-world signals such as speech (Speech Processing) and images (Image Processing).
A visitor looking to find the Signal Processing Division’s DSP Laboratory is encouraged to follow the rich aroma of freshly-brewed filter coffee, the substance that fuels approximately 30 post-graduate researchers in our well-equipped laboratories. Since so much of our research involves the manipulation of information, the main work area is a large computer network running Ubuntu Linux. The division also maintains three smaller laboratories for specialised equipment and hardware development. Five full-time faculty members oversee the research effort.

The activities in the Signals Division can be divided into five primary research areas, each with its own projects and staff members.
Contact person: TR Niesler: trn@sun.ac.za OR Tel: +27-21-808 4118

Speech Processing

Image Processing

Satellite Communications

Software Defined Radio

Network Applications

The Media Lab

Exchange Opportunities

Signal Processing Group
Digital Signal Processing GroupWe are a research group within the Department of Electrical and Electronic Engineering concerned with Digital Signal Processing. Yearly we attract numerous postgraduate engineering students studying towards their Masters and PhD degrees. The group has many areas of particular focus and research targeting signal processing of various kinds. These include speech recognition, image processing, broadcasting, network protocols, under-water communication and software defined radio.


Handwriting Analysis Group

The Recovery of Dynamic Information from Static Handwritten Scripts. The problem of estimating dynamic information from static handwritten scripts is a joint effort between the following groups:
The Applied Mathematics group of the Department of Mathematical Sciences at the University of Stellenbosch in South Africa.
The Digital Signal Processing (DSP) group of the Department of Electronic Engineering at the University of Stellenbosch in South Africa.


Software Defined Radio Group

Software Defined Radio Group

Software Defined Radio (SDR) is a communications architecture where maximum system functionality (including modulation and demodulation) is seated in the digital, or software, domain. This approach promises highly flexible communication systems, where a single hardware platform can be reused for many different applications, and system upgrades can be done through a simple software update. Also, the main focus of system design shifts to software, allowing rapid application development and implementation.
The SDR Research Group is a group of postgraduate engineering students of the University of Stellenbosch. The group focuses on the development of a software library for use in SDR-related projects, with an object-oriented architecture to facilitate fast and flexible application design.

Prof JA (Johan) DU PREEZ

Prof JA (Johan) DU PREEZ

Professor
Dr HA (Herman) ENGELBRECHT

Dr HA (Herman) ENGELBRECHT

Senior Lecturer
Prof TR (Thomas) NIESLER

Prof TR (Thomas) NIESLER

Professor
Email: trn@sun.ac.za
Tel: 021-808 4118
Website: http://www.dsp.sun.ac.za/~trn/
Dr R (Riaan) WOLHUTER

Dr R (Riaan) WOLHUTER

Senior Researcher
Email: wolhuter@sun.ac.za
Tel: 021-808 4343
Website: http://staff.ee.sun.ac.za/rwolhuter

Gateways


Industry links


Latest in Jobshop

Latest Events

First icon box

2016 PRASA-RobMech International Conference

November 30, 2016 – December 2, 2016

First icon box

Antennas for Radio Telescopes – 2016

November 21, 2016 – November 25, 2016