FORMAL COMPUTATIONAL SKILLS

Course outline, Autumn 2005

Tutor

Andrew Philippides
Email: andrewop@sussex.ac.uk.

Aims

The aim of this course is to provide the mathematical background needed to understand several subjects which appear in Informatics MSc courses. In particular, the course is a pre-requisite for students taking the 2nd term courses: Neural Networks and Computational Neuroscience.

Teaching method

Lectures will give mathematical details and theory on a particular subject. Seminars will (mainly) be practical computer classes which reinforce the theory using a topic from future courses. As the mathematical background of the group will be mixed, the lectures will start at an introductory level and so not all students will need to attend.

Lectures:
Mondays 10-10.50 Chichester 3 3R143
Tuesdays 9-9.50 Chichester 3 3R143

Seminars:
Tuesdays 2-2.50 Pevensey 1 1A09: for students who DO NOT have a clash at this time
Thursdays 12-12.50 Pevensey 1 1A09: for students who cannot make the Tuesday lecture
Fridays 11-11.50 Pevensey 1 1A09: for anyone who hasn't finished the coursework

Topics covered

Topics in italics are likely to be used to illustrate the mathematical techniques. Not everything will be discussed at the same level of detail.

Week 4

Matlab. Central limit Theory
[Work sheet and notes (word)] [Work sheet and notes (pdf)]
[Example m-files (zip)]

THIS WEEK'S PROBLEM SHEET IS THE LAST 2 PAGES OF THE WORK SHEET

Week 5

Main project details and project ideas. Programming networks in matlab.
[Notes (ppt)] [Notes (html)]
[Problem Sheet (pdf)]

Week 6

Differential calculus, partial differentiation. Gradient Descent.
[Lecture notes (ppt)] [Lecture notes (html)]
[Problem Sheet (pdf)] [GradientAscentEg.m]

Week 7

Numerical methods for integration of differential equations. Numerical integration of a model neuron
[Lecture notes (ppt)] [Lecture notes (html)]
[Problem Sheet (pdf)]

Week 8

Dynamical systems analysis. Analysis of GasNet neurons.
[Lecture notes (ppt)] [Lecture notes (html)]
[Cobweb plots (doc)] [Cobweb plots (pdf)]
[Problem Sheet (pdf)] [GasNetEgs.m]

Week 9

Probability and distributions. Entropy and information theory.
[Lecture notes (ppt)] [Lecture notes (html)]
No problem sheet this week.

Week 10

Optimisation and introduction to hypothesis testing. Analysis of data from A-life experiments.
[Lecture notes (ppt)] [Lecture notes (html)]
No problem sheet this week.

Assessment

The course is assessed by coursework only. 50% of the mark is for problem sheets undertaken throughout the term and 50% for a project to be handed in at the end of term. The project is to describe/explain a mathematical subject relevant to the courses you are undertaking in the rest of the course. Topics must be agreed with me.

Main project is to be handed in on Thursday 8th December (last week of term) by 4pm. Details given in lecture in week 5.

Warning: The lecture notes are not meant as an exhaustive resource about the given subjects. They may be modified before each lecture. They may also contain typographic errors: please let me know if you find any.

Reading

Notes on some of the topics covered are available in HTML and in PDF. Further reading is suggested in the appropriate sections of the notes.