2020/21 Undergraduate Module Catalogue

ELEC1703 Algorithms and Numerical Mathematics

10 creditsClass Size: 100

Module manager: Dr. Dragan Indjin
Email: d.indjin@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2020/21

This module is mutually exclusive with

ELEC1701

Introduction to Engineering Mathematics

This module is not approved as a discovery module

Module summary

The teaching and assessment methods shown below will be kept under review during 2020-21. In particular, if conditions allow for alternative formats of delivery, we may amend the timetable and schedule appropriate classes in addition to (or in place of) the Online Learning Workshops. For Semester 2 (from January 2021), we anticipate that this will be most likely, in which case online teaching will be substituted for traditional face-to-face teaching methods, including lectures and practical classes. ‘Independent online learning’ will involve watching pre-recorded lecture material or screen-casts, engaging in learning activities such as online worked examples or remote/virtual laboratory work, etc. Students will be expected to fully engage with all of these activities. The time commitment for independent online learning, and also the frequency and duration of Online Learning Workshops, are approximate and intended as a guide only. Further details will be confirmed when the module commences.

Objectives

This module introduces students to the concepts of logical algorithm design and numerical mathematics, and the application of logical algorithms to solve numerical mathematics problems.

Learning outcomes
On completion of this module students should be able to:

1. Design simple algorithms to perform logical and numerical operations.
2. Understand and apply numerical methods for differentiation, integration, curve fitting and root finding.
3. Use Matlab functions and the Matlab programming language to implement numerical mathematics solutions.
4. Use numerical methods to solve simple matrix problems.
5. Use numerical methods to solve simple matrix problems.

Syllabus

Topics may include, but are not limited to:

Introduction to the logic of programming and program structure
Standard conditional program clauses
Arrays and matrices
Array handling in Matlab
Algorithm design to solve numerical problems
Numerical integration: trapezium and Simpson’s rules
Numerical differentiation: finite difference method
Interpolation, curve-fitting and root-finding
Introduction to variational methods

Teaching methods

Delivery type	Number	Length hours	Student hours
On-line Learning	3	2.00	6.00
Independent online learning hours			32.00
Private study hours			62.00
Total Contact hours			6.00
Total hours (100hr per 10 credits)			100.00

Private study

Students are expected to use private study time to consolidate the material covered in lectures, to undertake preparatory work for laboratory classes and to prepare for summative assessments.

Opportunities for Formative Feedback

Students receive feedback on their progress through the initial assignments.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Online Assessment	Online Assignment/Test 1	30.00
Online Assessment	Online Assignment/Test 2	30.00
Online Assessment	Online Assignment/Test 3	40.00
Total percentage (Assessment Coursework)		100.00

Resits for ELEC and XJEL modules are subject to the School's Resit Policy and the Code of Practice on Assessment (CoPA), which are available on Minerva. Students should be aware that, for some modules, a resit may only be conducted on an internal basis (with tuition) in the next academic session.

Reading list

There is no reading list for this module

Last updated: 10/08/2020 08:35:35

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