Abstract
A diffusion can be thought of as a strong Markov process (in ℝn) with continuous paths. Before the development of Itô’s theory of stochastic integration for Brownian motion, the primary method of studying diffusions was to study their transition semigroups. This was equivalent to studying the infinitesimal generators of their semigroups, which are partial differential operators. Thus Feller’s investigations of diffusions (for example) were actually investigations of partial differential equations, inspired by diffusions.
Keywords
- Brownian Motion
- Stochastic Differential Equation
- Standard Brownian Motion
- Local Martingale
- Finite Variation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2005 Springer-Verlag Berlin Heidelberg
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Protter, P.E. (2005). Stochastic Differential Equations. In: Stochastic Integration and Differential Equations. Stochastic Modelling and Applied Probability, vol 21. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-10061-5_6
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DOI: https://doi.org/10.1007/978-3-662-10061-5_6
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Print ISBN: 978-3-642-05560-7
Online ISBN: 978-3-662-10061-5
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