
Academic Year:  2014/5 
Owning Department/School:  Department of Computer Science 
Credits:  6 
Level:  Intermediate (FHEQ level 5) 
Period: 
Semester 2 
Assessment Summary:  CW 25%, EX 75% 
Assessment Detail: 

Supplementary Assessment: 
CM20220A Mandatory Extra Work (where allowed by programme regulations) 
Requisites:  Before taking this unit you must take CM10197 
Description:  Aims: To provide mathematical foundations underpinning concepts of digital signal processing (DSP), probabilistic methods and search/optimization algorithms demanded by Pattern Recognition, Computer Vision and Sound. Learning Outcomes: On completion of this unit students will be able to: 1. understand and apply common signal processing operations, understanding their effect in terms of spatial and frequency domain. 2. understand and apply basic probabilistic methods to infer meaning from images. 3. understand and apply appropriate search strategies and optimization technique to solve Computer Vision problems. Skills: Problem Solving (T/F, A), Application of Number (T/F, A). Content: FUNDAMENTALS OF DIGITAL SIGNAL PROCESSING (DSP) * Frequency space  Continuous and Discrete Fourier transform (1D and 2D).  Discrete signal and image representation. Aliasing.  Taylor expansion * Digital signal processing (1D and 2D)  Convolution theorem  Low pass filters and antialiasing. Overview of high pass filters.  Image transformation, interpolation PROBABILITY AND PATTERN CLASSIFICATION * Means, standard deviation and variance. * Bayes theorem. Bayesian Inference. Priors. * Principal Component Analysis. Eigenmodels. * Classification  Concept of a feature space  Distance metrics  Supervised vs. Unsupervised learning. * Gaussian Mixture Models SEARCH AND OPTIMIZATION * Deterministic methods  Least squares  Best first, Gradient descent * Stochastic methods  kmeans  Simulated annealing  Evolutionary search e.g. genetic algorithms 
Programme availability: 
CM20220 is Compulsory on the following programmes:Department of Computer Science
