Applied Stochastic Processes in Science and Engineering
by Matt Scott
Publisher: University of Waterloo 2013
Number of pages: 316
This book is designed as an introduction to the ideas and methods used to formulate mathematical models of physical processes in terms of random functions. Written for a senior undergraduate course offered to students with a suitably mathematical background.
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by 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.
by Anders Szepessy, et al. - KTH
The goal of this course is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and finance. Typically, these problems require numerical methods to obtain a solution.
by Daniel W. Stroock - Tata Institute of Fundamental Research
The author's purpose in these lectures was to provide some insight into the properties of solutions to stochastic differential equations. In order to read these notes, one need only know the basic Ito theory of stochastic integrals.
by Jan A. Van Casteren - Bookboon
In this book, which is basically self-contained, the following topics are treated thoroughly: Brownian motion as a Gaussian process, Brownian motion as a Markov process, Brownian motion as a martingale, Markov chains, renewal theory, etc.