Advanced engineering mathematics
| Code | School | Level | Credits | Semesters |
| EEEE3107 | Department of Electrical and Electronic Engineerin | 3 | 10 | Autumn China |
- Code
- EEEE3107
- School
- Department of Electrical and Electronic Engineerin
- Level
- 3
- Credits
- 10
- Semesters
- Autumn China
Summary
This module provides an introduction to a variety of mathematical techniques that are used in advanced electrical and electronic engineering. The content includes:
Signal processing: Transforms allow data to be represented in different ways; Useful if more efficient – or enhances
aspect of the data; Recap Discrete Fourier Transform; Other Discrete Transforms (Hartley, Haar, Discrete Cosine);
Karhunen Loeve Transform / Principal Component Analysis; KLT / PCA; Empirical Mode Decomposition (Hilbert Hu
transform).
PDEs: The origin of Partial Differential Equations drawn from a range of engineering examples and consideration of
techniques used to solve them.
Matrices: Review of basic matrix notation and operations and the consideration of: Special structures and methods
diagonal and triangular forms; Linear equation solving; Eigenproblems and related decompositions; Special techniq sparse problems.
Reassessment of this module, if required, will be by 100% exam.
Target Students
Part II students on courses offered by Department of Electrical and Electronic Engineering
Classes
- One 2-hour workshop each week for 5 weeks
- One 2-hour lecture each week for 12 weeks
Assessment
- 25% Coursework1
- 75% Exam (2-hour)
Assessed by end of autumn semester
Educational Aims
To provide of knowledge of advanced mathemacal techniques and their relevance to Electronic Engin applicaonsLearning Outcomes
By the end of the module, students should be able to:
LO1 Translate engineering problems into a mathematical framework.
LO2 Apply advanced techniques in mathematics to solve problems typical of those found within an electrical, electronic and/or computer engineering context.
LO3 Use suitable techniques for representing engineering problems and be able to select suitable approaches for extracting particular information.
LO4 Select suitable schemes for modelling engineering scenarios and their associated data; be able to apply key algorithms for manipulating these representations with consideration of issues of computational efficiency and fidelity.
This module contributes to the delivery of the following Engineering Council outcomes:
C1, C2, C3, C13
Conveners
- Dr Chengbo Wang