Stochastic Differential Equations: Models and Numerics
by Anders Szepessy, et al.
Publisher: KTH 2010
Number of pages: 202
Description:
The goal of this course is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and mathematical finance. Typically, these problems require numerical methods to obtain a solution and therefore the course focuses on basic understanding of stochastic and partial differential equations to construct reliable and efficient computational methods.
Download or read it online for free here:
Download link
(2.3MB, PDF)
Similar books
Reversibility and Stochastic Networksby F.P. Kelly - John Wiley and Sons Ltd
The book on vector stochastic processes in equilibrium or stochastic networks, with wide range of applications. It covers the concept of reversibility, the output from a queue, and the epolymerization process quilibrium distribution.
(19310 views)
Synchronization and Linearity: An Algebra for Discrete Event Systemsby F. Baccelli, G. Cohen, G. J. Olsder, J. Quadrat - John Wiley & Sons
Presents new modelling and analysis techniques for the description of discrete event dynamic systems. Created within the text is a calculus which allows the derivation of analytical tools for computing the time behavior of this type of system.
(16902 views)
Lectures on Singular Stochastic PDEsby M. Gubinelli, N. Perkowski - arXiv
The aim is to introduce the basic problems of non-linear PDEs with stochastic and irregular terms. We explain how it is possible to handle them using two main techniques: the notion of energy solutions and that of paracontrolled distributions.
(8327 views)
Introduction to Stochastic Processesby Gordan Žitković - The University of Texas at Austin
Contents: Probability review; Mathematica in 15 minutes; Stochastic Processes; Simple random walk; Generating functions; Random walks - advanced methods; Branching processes; Markov Chains; The 'Stochastics' package; Classification of States; etc.
(9726 views)