AMH1 Computational Projects in Applied Mathematics
General Information
This page relates to the Applied Mathematics Honours course "Computational Projects in Applied Mathematics".
Lecturer for this course: David Ivers.
For general information on honours in the School of Mathematics and Statistics, refer to the relevant honours handbook.
Resources
The information sheet (Mar 24 update) outlines the course projects for assessment and their due dates.
Guidelines for writing up the report are outlined in the report style sheet.
Project  Lecture notes  Matlab codes  Material covered  

Week 1 
Rabies in foxes 
Problem formulation IVP's and timestepping 

Week 2 
Project 1 Rabies in foxes 
Multistep, finitedifferences, FTCS scheme Method of lines, Project 1 

Week 3 
Spectral methods for nonlinear wave equations 
Project 1 (end) Discrete Fourier transform Fast Fourier transform, Project 2, spectral methods for de's 

Week 4 
Applications of the singular value decomposition 
Fourier transform (more) Project 2 (end) Project 3, singular value decomposition 

Week 5 
The expulsion of magnetic flux by convective eddies (advection of a passive scalar) 
Singular value decomposition (more), Project 3 (end) Project 4, magnetic induction equation in 2D, flux expulsion 

Week 6 
Project 4 Expulsion of magnetic flux 
No lecture 
Fluxconservative leapfrog scheme, weak diffusion Project 4 (end) 

Week 7 
Symplectic integration 
No lecture 
Symplectic integration 

Week 8 
No lectures 

Week 9 
Project 5 Stochastic DE's 
Numerical symplectic integration, Project 5 (end) Stochastic DE's, Wiener processes Numerical integration schemes 

Week 10 
Project 6 Neural Networks 
Numerical integration schemes, Project 6 (end) Neurons, layers, learning, feedforward networks Numerical learning schemes, Project 7 (end) 
Timetable
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