This module is offered in 2023-24.


The aims of this module are:

  • To introduce signal processing concepts for use in time series data (such as sound), and matrix data (such as images and videos).

Learning Outcomes

On successful completion of this module, the student should:

  • Be familiar with various signal processing concepts, such as frequency analysis using Fourier Transforms.
  • Have gained experience in programmatically processing signals (including both signals and images).
  • Have gained an understanding of how humans perceptive signals and how this affects the computational signal processing we perform.
  • Understand the issues that arise when designing and building signal processing pipelines.


This module covers the fundamentals of signal processing and perception: investigating how sounds, images and videos can be processed and analysed alongside the fundamentals of how the human auditory and visual perception system functions (e.g., how your eyes and ears work with your brain). Concepts such as data encoding and compression are provided with practical application of understanding signals in terms of their frequency components, relating to their time and spatial components (e.g., audio frequency components or the spatial frequency of an image). Using a programming language regularly used in image and signal processing, students will gain practical skills in applying concepts to real-world problems, including using Fourier transforms, to calculate the frequency distribution in audio files, and undertake tasks such as reducing noise from signals. This module is useful for those wanting to move into the fields of computer vision or data analysis.

Compulsory Elements

This module has no compulsory elements beyond those common to all modules (mark of 4 in each assessment component).

Module Delivery

Module Coordinator

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Last Published: 02 Apr 2024.