In this paper, we investigate backward stochastic differential equations driven by G-Brownian motion with uniformly continuous coefficients in (y, z). The existence and uniqueness of solutions are obtained via a method of Picard iteration, a linearization method and a monotone convergence argument. Furthermore, we establish the corresponding comparison theorem and related nonlinear Feynman–Kac formula.

中文翻译：

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(y, z) 中具有一致连续系数的 G-Brown 运动驱动的后向随机微分方程

在本文中，我们研究了由G -Brownian 运动驱动的后向随机微分方程，其系数在 ( y ,  z ) 中具有均匀连续的系数。通过Picard迭代法、线性化法和单调收敛论证获得解的存在性和唯一性。此外，我们建立了相应的比较定理和相关的非线性Feynman-Kac公式。