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Stochastic Differential Equations
2014Stochastic differential equations describe the time evolution of certain continuous n-dimensional Markov processes. In contrast with classical differential equations, in addition to the derivative of the function, there is a term that describes the random fluctuations that are coded as an Ito integral with respect to a Brownian motion. Depending on how
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Stochastic differential equations
Stochastic differential equations serve as the foundation for many sections of applied sciences, such as mechanics, statistical physics, diffusion theory, cosmology, financial mathematics, economics, etc. The number of works devoted to various issues related to specific equations considered in individual areas of science listed above is very large.openaire +2 more sources
Stochastic Differential Equations
1991In previous chapters stochastic differential equations have been mentioned several times in an informal manner. For instance, if M is a continuous local martingale, its exponential e(M) satisfies the equality $$\mathcal{E}{(M)_t} = 1 + \int_0^t {\mathcal{E}{{(M)}_s}} d{M_s};$$ this can be stated: e(M) is a solution to the stochastic differential
Daniel Revuz, Marc Yor
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On stochastic differential equations
Memoirs of the American Mathematical Society, 1951openaire +1 more source
Impedance Analysis of Electrochemical Systems
Chemical Reviews, 2022Vincent Vivier, Mark E Orazem
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Colloidal Self-Assembly Approaches to Smart Nanostructured Materials
Chemical Reviews, 2022Zhiwei Li Li, Yadong Yin
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Detection methods for stochastic gravitational-wave backgrounds: a unified treatment
Living Reviews in Relativity, 2017Joseph D Romano, Neil Cornish
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Physiological heterogeneity in biofilms
Nature Reviews Microbiology, 2008Philip S Stewart, Michael J Franklin
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Benchmarking the performance of all-solid-state lithium batteries
Nature Energy, 2020Dominik A Weber +2 more
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