Advanced Engineering Mathematics
| Code | School | Level | Credits | Semesters |
| EEEE3090 | Electrical and Electronic Engineering | 3 | 10 | Spring UK |
- Code
- EEEE3090
- School
- Electrical and Electronic Engineering
- Level
- 3
- Credits
- 10
- Semesters
- Spring UK
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 some 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 Huang transform).
PDEs: The origin of Partial Differential Equations drawn from a range of engineering examples and consideration of the techniques used to solve them.
Matrices: Review of basic matrix notation and operations and the consideration of: Special structures and methods using the diagonal and triangular forms; Linear equation solving; Eigenproblems and related decompositions; Special techniques for sparse problems.
Reassessment of this module, if required, will be by 100% exam.
Target Students
Year 3 MEng students in the Department of EEE
Classes
- One 2-hour lecture each week for 11 weeks
Assessment
- 25% Coursework
- 75% Exam (2-hour)
Educational Aims
To provide of knowledge of advanced mathematical techniques and their relevance to Electronic Engineering applications.Learning 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, M1, C2, M2, C3, M3, C13 and M13
Conveners
- Prof Phillip Donald Sewell