2021/22 Undergraduate Module Catalogue

XJEL1703 Algorithms and Numerical Mathematics

10 creditsClass Size: 75

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

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2021/22

This module is not approved as a discovery module

Module summary

The teaching and assessment methods shown below will be kept under review during 2021-22. If it is not possible to deliver traditional teaching methods, such as lectures and practical classes, we may need to substitute alternative (online) formats of delivery and amend the timetable accordingly. ‘Independent online learning’ may involve watching pre-recorded lecture material or screen-casts, engaging in learning activities such as online worked examples or mini-projects, 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 sessions are approximate and intended as a guide only. Further details will be confirmed when the module commences.Where assessments are shown as Online Time-Limited Assessments, the durations shown are indicative only. The actual time permitted for individual assessments will be confirmed prior to the assessments taking place.

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. Apply numerical methods for differentiation, integration, curve fitting and root finding.
3. Use Matlab functions and the Matlab programming language to implement numerical solutions to well-defined problems.
4. 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
Laboratory	8	2.00	16.00
Lecture	16	1.00	16.00
Private study hours			68.00
Total Contact hours			32.00
Total hours (100hr per 10 credits)			100.00

Private study

Students are expected to use private study time to consolidate their understanding of course materials, to undertake preparatory work for seminars, workshops, tutorials, examples classes and practical classes, and also to prepare for in-course and summative assessments.

Opportunities for Formative Feedback

Students studying ELEC modules will receive formative feedback in a variety of ways, including the use of self-test quizzes on Minerva, practice questions/worked examples and (where appropriate) through verbal interaction with teaching staff and/or post-graduate demonstrators.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Assignment 1	30.00
Assignment	Assignment 2	70.00
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: 29/06/2021 16:47:30

Disclaimer

Browse Other Catalogues

• Undergraduate module catalogue
• Taught Postgraduate module catalogue
• Undergraduate programme catalogue
• Taught Postgraduate programme catalogue

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD