PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Tutorial Introduction to Stochastic Differential Equations: Continuous-time Gaussian Markov Processes
Christopher Williams
In: Dynamical Systems, Stochastic Processes and Bayesian Inference, 9 Dec 2006, Whistler, BC, Canada.


Abstract: - AR processes, Langevin equations, SDEs - Wiener process, simulation of SDEs, simple examples - Infinitesimal first and second moments (Diffusion processes) - Stationary processes---calculation of cov function/power spectrum - Computing conditional distributions given initial conditions - Brief discussion of Fokker-Planck equations

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EPrint Type:Conference or Workshop Item (Tutorial)
Additional Information:A video of this lecture is available at
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:3444
Deposited By:Christopher Williams
Deposited On:11 February 2008