Module ICM-3004:
Signal Processing

Module Facts

Run by School of Computer Science and Electronic Engineering

10 Credits or 5 ECTS Credits

Semester 1

Organiser: Dr Iestyn Pierce

Overall aims and purpose

To introduce the concepts of digital signal processing and transducers. To enable students to analyse and design simple digital processing systems.

Course content

Content:

• Time and frequency response of linear systems, Z-transform; Continuous and discrete signals; Sampling theory; Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT); Digital Signal Processing (DSP) theory and systems; FIR and IIR filters; Deterministic and stochastic signals; Classical spectral estimation; Analogue to Digital Conversion.

• Limitations of FIR and IIR filter design methods; Effects of finite word length and sampling on DSP systems; Effect of windowing and averaging on spectral estimation.

• Design methods for FIR and IIR filters; Design of spectral estimation systems.

Learning outcomes mapped to assessment criteria

  threshold

40%

good

60%

excellent

70%

Know and understand the characteristics and mathematical basis of a digital signal processing system and transducers, and how the characteristics relate to analogue input signals and to equivalent analogue systems.

Has basic knowledge and understanding of: the essential characteristics of a DSP system, digital signals and their relationship to analogue signals, the relationship between DSP and analogue systems. Has knowledge and understanding of most of the material covered. In addition to the threshold requirements understands the implications of the theoretical background In-depth understanding of all areas covered. Can evaluate results and derivations sensibly.

Understand the main limitations and sources of error in digital signal processing systems and methods of minimising their effect.

Has a basic understanding of the limitations and sources of error in a DSP system and methods of minimising their effect in simple systems Understands most of the limitations and sources of error in a DSP system and methods of minimising their effects in higher order systems In-depth understanding of all areas covered. Evaluates designs for correctness and fitness for purpose

Carry out systematic analysis and design of example digital signal processing systems

Able to analyse and design simple (first order) filters and basic spectral estimators. Able to analyse and design simple (first order) systems and most aspects of higher order systems and more complex spectral estimators. Able to analyse unseen systems and design high order systems to unseen specifications

Assessment Methods

Type Name Description Weight
EXAM Examination 100

Teaching and Learning Strategy

Hours
Private study

Worked examples, tutorial problems, and revision.

76
Lecture

2 x 1 hour lectures per week for 12 weeks.

24

Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Subject specific skills

  • Identify emerging technologies and technology trends;
  • Apply underpinning concepts and ideas of engineering;
  • Formulate and analyse requirements and practical constraints of products, processes and services, place them in an engineering context and manage their implementation;
  • Solve problems logically and systematically;
  • Assess and choose optimal methods and approaches for the specification, design, implementation and evaluation of engineering solutions.
  • Access and synthesize information and literature sources;
  • Analyse and display data using appropriate methods and mathematical techniques;

Courses including this module

Compulsory in courses: