This unit will introduce students to matrix decomposition methods including singular value decomposition with applications including data compression, image processing, noise filtering, and finding exact and approximate solutions of linear systems. Numerical methods for working efficiently with large matrices and handling ill-conditioned data will be discussed. Methods for unconstrained and constrained optimisation will be presented, with use of MATLAB. The second half of the unit will focus on stochastic processes inboth discrete and continuous time, with applications to time series modelling, and circuit analysis. -- Course Website
Instructor: Professor Kate Smith-Miles (Clayton), Mr Nader Kamrani (Sunway)
Prerequisites: ECE2011, ENG2092
