Taught course

Digital Signal Processing

Queen Mary, University of London · Electronic Engineering

Entry requirements

You should have a first or upper second class degree in electronic engineering, computer science, mathematics, or a related discipline. You should have programming experience from your undergraduate degree.

Applicants with unrelated degrees will be considered if there is evidence of significant industrial experience. Applicants with lower second class degrees may be considered if the undergraduate degree specialised in relevant subjects.

Applicants should also have completed an undergraduate programme in at least one of the following areas: signal processing, control or analogue filters.

Months of entry


Course content

Programme description
This programme is specifically intended to respond to a growing skills shortage in industry for engineers with a high level of training in signal processing, and to support Internet, multimedia, broadcast, communications, and consumer industries.

You will develop core knowledge of basic DSP theory and its implementation in hardware. In addition you will be able to specialise in areas including multimedia and intelligent signal processing. The taught modules are fully supported, with computing and laboratory work. The MSc is intended for graduates in a related discipline, who wish to enhance and specialise their skills in the area, and also for industrialists with some experience of working with signal processing in the IT sector, who wish to obtain a formal qualification.

Programme outline
Core modules:

  • Fundamentals of DSP (1)
  • Advanced Transform Methods
  • Multimedia Systems
  • Music And Speech Processing
  • Image And Video Processing
  • Machine Learning

Module options:

  • Real Time Digital Signal Processing
  • Digital Broadcasting
  • C++ For Image Processing

(1) = This module is taken in the first year of part-time by distance learning study.

Please note module availability is subject to change.

Qualification and course duration


full time
12 months
part time
24 months

Course contact details

Rupal Vaja, Postgraduate Administrator
+44 (0)20 7882 7335