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BEng Electronic Engineering with Industrial Experience / Course details

Year of entry: 2024

Course unit details:
Numerical Analysis

Course unit fact file
Unit code EEEN30101
Credit rating 10
Unit level Level 3
Teaching period(s) Semester 1
Available as a free choice unit? No

Overview

Brief description of the unit:

The unit gives an introduction to numerical methods that are routinely used by engineers in analysis and design. 

Topics will include: root finding and optimization; solving linear algebraic systems; curve fitting; numerical integration and differentiation; numerical solutions of simple ordinary differential equations and partial differential equations.

There will be an emphasis on numerical accuracy, numerical stability and computational efficiency.  Meanwhile the techniques will be illustrated on examples from the Electrical and Electronic Engineering, Electronic Engineering and Mechatronic Engineering streams.  These will include: circuit analysis, power flow optimization; digital signal processing; plotting V/I characteristics; finding transfer function poles; realizing transfer function responses.

Lecture material will be illustrated with Matlab examples.  Students are encouraged to implement the techniques on other software platforms.

 

Pre/co-requisites

Unit title Unit code Requirement type Description
Signals and Systems EEEN20131 Pre-Requisite Compulsory
Mathematics 2E1 MATH29681 Pre-Requisite Compulsory

Aims

This course unit detail provides the framework for delivery in the current academic year and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates.

The course unit unit aims to:

  • Reinforce students' confidence in using Matlab and other software platforms suitable for numerical analysis.
  • Give an overview of numerical methods routinely used by electrical, electronic and mechatronic engineers.
  • Illustrate their application on examples encountered in other 1st, 2nd and 3rd year units.

Learning outcomes

On the successful completion of the course, students will be able to:

Developed

Assessed

ILO 1

Calculate numerical solutions to integration problems and the time evolution of simple dynamical systems

x

X

ILO 2

Code simple algorithms for root finding, LU decomposition and least squares

x

X

ILO 3

Solve simple line fitting and optimization problems

x

X

ILO 4

Explain the role of randomisation for non-convex optimisation problems

x

X

ILO 5

Analyse numerical accuracy in the context of floating point arithmetic and determine suitable stopping criteria for numerical computation

x

X

ILO 6

Factorize matrices and interpret their rank, condition number and singular values in terms of linear algebraic equations modelling physical applications

x

X

ILO 7

Write code for numerically efficient matrix computation

x

X

 

Teaching and learning methods

Standard lecture and laboratory format, but with an emphasis on numerical examples and applications.

 

Assessment methods

Method Weight
Other 20%
Written exam 80%

Coursework

Coursework forms 20% of the unit assessment

Assignments related to both the laboratory sessions

 

Feedback methods

.  

Recommended reading

S C Chapra. Applied Numerical Methods with MATLAB for Engineers and Scientists, 3rd edition, McGraw-Hill 2012

Study hours

Scheduled activity hours
Lectures 20
Practical classes & workshops 6
Tutorials 4
Independent study hours
Independent study 70

Teaching staff

Staff member Role
Eduardo Martinez Cesena Unit coordinator
Sareh Malekpour Unit coordinator

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