We study the stochastic total variation flow (STVF) equation with linear multiplicative noise. By considering a limit of a sequence of regularized stochastic gradient flows with respect to a regularization parameter $\varepsilon$ we obtain the existence of a unique variational solution of the STVF equation which satisfies a stochastic variational inequality. We propose an energy preserving fully discrete finite element approximation for the regularized gradient flow equation and show that the numerical solution converges to the solution of the unregularized STVF equation. We perform numerical experiments to demonstrate the practicability of the proposed numerical approximation. This paper contains a mistake: in the proof of Lemma 4.4 the last inequality is not valid. Meanwhile, this mistake has been fixed in [6] for a slightly modified numerical approximation in spatial dimension $d=1$. For $d\geq 1$ the validity of the estimate in Lemma 4.4 is still open but the convergence of the numerical approximation can be shown by a different approach, see [5].
翻译:我们用线性倍增噪声研究随机总变差流(STVF)方程式。 通过考虑对一个正规化参数($\varepsilon$)进行常规化梯度流的序列限制, 我们获得了STVF方程式的独特变异解决方案, 满足了随机化变异性不平等。 我们建议为正常化梯度流方程式提供一个完全离散的有限元素近似值, 并显示数字方程式与非常规化的STVF方程式的解决方案相融合。 我们进行了数字性实验, 以证明拟议的数字近似值是否可行。 本文包含一个错误: 在Lemma 4. 4 的证明中, 最后一个不平等是无效的。 同时, 这一错误被固定在[6] 中, 以空间维度略微修改的数字近似值($d=1美元) 。 Ford\geq 1美元中估算值的有效性仍然开放, 但数字近值的趋同可以通过不同的方法显示, 见 [5] 。