Examples of 'stochastic differential' in a sentence
Meaning of "stochastic differential"
stochastic differential: Stochastic differential refers to a mathematical equation that involves randomness or unpredictable factors. It is often used in fields such as physics, finance, and engineering to model systems with random variables and study their behavior over time
How to use "stochastic differential" in a sentence
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stochastic differential
An attempt to modeling by a stochastic differential equation is proposed.
On stochastic differential equations.
These particules satisfy stochastic differential equations.
Stochastic differential equations and their applications in financial mathematics and biology.
The explicit solution of this stochastic differential equation is.
As a stochastic differential equation.
The involved dynamics is formulated as a stochastic differential equation.
A variety of stochastic differential games are formulated and explicitly solved.
It has important applications in mathematical finance and stochastic differential equations.
Mathematical models based on stochastic differential equations in determining the market value of options.
Analytic and numeric approximations to solutions of perturbed stochastic differential equations.
The second model is related to a stochastic differential equation and has never been proposed before.
Undistinguishable means that every agent is governed by the same stochastic differential equation.
Stochastic calculus provides a notion of stochastic differential and an associated calculus for stochastic processes.
Skorohod obtained general results for solutions unboundedness for an autonomous stochastic differential equation.
See also
I think all solutions to stochastic differential equations involve Gaussians.
This permits a pathwise definition of the Itô Integral and pathwise solutions of stochastic differential equations.
This takes the form of a stochastic differential equation with a Brownian motion of small dimension.
The first one deals with the models described by stochastic differential equations.
Anticipating Stochastic differential equations.
Spatio-temporal covariance functions are formulated as infinite-dimensional stochastic differential equations.
Stochastic differential equation, unbounded of solution, regularly varying functions.
This is described by a matrix-valued stochastic differential equation.
The stochastic differential equation was discretized and solved by the euler-maruyama method adequately.
He works on stochastic analysis, stochastic differential equations and geometric analysis.
Stochastic differential equations and diffusions; 2.
The resulting model, in terms of a stochastic differential equation, is solved analytically.
This is done for one-dimensional (temporal) covariance functions and linear time-invariant stochastic differential equations.
Wiener process, martingales, stochastic differential equations and applications in financial mathematics and biology.
The Euler-Maruyama method for the numerical solution of stochastic differential equations bears his name.
Consider the stochastic differential equation ( see Itô calculus ).
The Tsirelson drift, a counterexample in the theory of stochastic differential equations.
One option was to apply Stochastic differential equations ( SDEs ) to the problem.
Stochastic differential equations, the Ito integral, and the Ito formula.
In the first part, three uses of backward stochastic differential equations are presented.
Abstract, We consider systems of stochastic differential equations involving two well-separated time scales.
This thesis also presents other solutions of the above stochastic differential equation $ ( SDE ) $.
Itō processes, which satisfy a stochastic differential equation of the form dX = σdW + μdt are semimartingales.
In the fourth part, we investigate advanced backward stochastic differential equations ( ABSDE ) with a jump.
The explicit solution of this stochastic differential equation is, formula 6.
Abstract, The analysis and approximation of soutions of Stochastic Differential Equations ( S.D.E. ).
Then, we study a class of scalar valued reflected stochastic differential equations driven by G-Brownian motion.
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