SHE Level 5
SCQF Credit Points 15.00
ECTS Credit Points 7.50
Module Code MMI123176
Module Leader Ryan Gibson
School School of Computing, Engineering and Built Environment
Subject Electronic Engineering
  • B (January start)

Summary of Content

The module provides knowledge of DSP theory, algorithms and techniques that are applicable to the design of contemporary real-time embedded systems. Topics in both classical and statistical DSP methods are covered including optimal filtering, spectral estimation and adaptive filtering with applications in analysis, communications and control.


Classical DSP algorithms Review of DSP fundamentals: the z-transform; the sampling theorem; anti-aliasing; signal quantisation, oversampling and dither; signal reconstruction; spectral analysis. FIR and IIR filters. Mechanics of implementation: digital filter realisations. Statistical Signal Processing Random Processes: probability, correlation, review of Linear Algebra. Adaptive filters: theory and applications. Optimal filtering: the Kalman filter, theory and applications. Algorithm optimisation Block Processing: Overlap Add/ Overlap Save. Buffering techniques. Mixed language programming. DSP design flows Classical design flows; schematic design; intellectual property DSP Platforms Traditional DSP architectures; Advance Multi-core DSP architectures ; FPGA architectures: FPGA implementation of digital filters, the role of FPGAs in the DSP chain

Learning Outcomes

On successful completion of this module the student should be able to:Ability to identify the primary constraints of real-time DSP applicationsTo describe and comprehend classical & statistical DSP algorithms and identify and evaluate types of applications for which they are suitableAbility to use industry standard tools for the development of real-time DSP applicationsKnowledge of, and ability to propose, appropriate design flows and platforms for real-time DSP systems

Teaching / Learning Strategy

The module will comprise lectures for the delivery of theoretical material that will be consolidated through laboratory demonstrations that place the material in context. Laboratory sessions will develop the ability to apply theoretical concepts within a practical development environment. Seminars will be used to explore design alternatives.

Indicative Reading

Books Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK (Topics in Digital Signal Processing), Chassaing & Reay , Wiley, 2008. Real-Time Digital Signal Processing; Kuo & Lee, Wiley 2006 DSP Software Development Techniques for Embedded and Real-Time Systems, Oshana, Newnes Publisher, 2006. N. Kehtarnavaz, Real-Time Digital Signal Processing : Based on the TMS320C6000, Elsevier, 2004. DIGITAL SIGNAL PROCESSING: A Computer Based Approach, Mitra, McGrawHill, 2011. Journals IEEE Transactions on Signal Processing IEE Proceedings Vision, Image & Signal Processing IEEE Signal Processing Magazine IEEE Transactions on Speech and Audio Processing

Transferrable Skills

Development of high level analytical and synthesis skills Development of independent learning skills Development of decision making skills Development of research skills

Module Structure

Activity Total Hours
Lectures (FT) 12.00
Practicals (FT) 24.00
Assessment (PT) 15.00
Tutorials (FT) 12.00
Practicals (PT) 24.00
Lectures (PT) 12.00
Tutorials (PT) 12.00
Assessment (FT) 15.00
Independent Learning (PT) 87.00
Independent Learning (FT) 87.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 1 n/a 30.00 45% Coursework only
Exam (Exams Office) 3.00 70.00 45% Exam - exams office