Strong convergence rates for full-discrete approximations of stochastic Burgers equations with multiplicative noise
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approximationsburgersconvergenceequationsestablishfull-discretemultiplicativenoise
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In this article we establish strong convergence rates on the whole probability space for explicit full-discrete approximations of stochastic Burgers equations with multiplicative trace-class noise. The key step in our proof is to establish uniform exponential moment estimates for the numerical approximations.
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Cited by 2 Pith papers
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Strong convergence of a fully discrete scheme for stochastic Burgers equation with fractional-type noise
A spectral Galerkin plus nonlinear-tamed accelerated exponential Euler scheme is proved to converge strongly for the stochastic Burgers equation with cylindrical fractional Brownian motion noise where H is in (1/2, 1).
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Strong convergence of an explicit full-discrete scheme for stochastic Burgers-Huxley equation
Proves strong convergence rates for a spectral Galerkin plus nonlinear-tamed exponential integrator scheme on the stochastic Burgers-Huxley equation.
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