Lecturer	Christina Orphanidou
Degrees	2009: Hilary Term — MSc in Mathematical Modelling and Scientific Computing
Term	Hilary Term 2009  (12 lectures)

Overview

The course introduces the mathematical techniques used and applied in modern signal processing systems; in particular focusing on linear transformations and linear algebra. Signal processing is the analysis and manipulation of signals including sound, image, video as well as biomedical signals such as the ECG, EEG and MRI. The course aims to introduce the main algorithms employed for performing operations on these signals, in either discrete or continuous time, such as data compression, denoising, filtering, event detection and identification, classification and a variety of other interesting and useful operations.

Synopsis

This course will consist of 12 lectures on the following topics:

1. Introduction to signal processing;
2. Signal formation and sampling in MRI and FMRI;
3. Representation of a signal in the frequency domain (Fourier methods);
4. Registration;
5. Compression (wavelets);
6. Segmentation;
7. Filter operations for attenuation of a signal;
8. Extracting information from a signal without a model (PCA,ICA);
9. De-noising;
10. Extracting information from a signal with a model (GLM, estimation theory);
11. Applications in speech and biomedical signal processing;
12. Applications in learning how the brain functions (FMRI).

Taking our courses

This form is not to be used by students studying for a degree in the Department of Computer Science, or for Visiting Students who are registered for Computer Science courses

Other matriculated University of Oxford students who are interested in taking this, or other, courses in the Department of Computer Science, must complete this online form by 17.00 on Friday of 0th week of term in which the course is taught. Late requests, and requests sent by email, will not be considered. All requests must be approved by the relevant Computer Science departmental committee and can only be submitted using this form.