A Method for Defining Gaussian Probability Densities for Forward Modeling in Finite Dimensions Using the Method of Tarantola

C. Clutz, A. Maniatty
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Abstract

The inverse problem of recovering an unknown boundary function given some information about the (interior) solution is considered. It is assumed that the forward problem is governed by a linear partial differential equation (PDE) and that homogeneous boundary conditions exist on the rest of the boundary. A method developed by Tarantola (Tar87) is used which is based upon statistical inference on finite dimensional random vectors. Within this framework, a method for constructing Gaussian probability density functions which model the forward problem is proposed.
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用Tarantola方法确定有限维正演高斯概率密度的方法
考虑给定(内部)解的一些信息,恢复未知边界函数的反问题。假设正演问题是由线性偏微分方程控制的,并且在边界的其余部分存在齐次边界条件。本文采用了Tarantola (Tar87)提出的基于有限维随机向量的统计推断的方法。在此框架下,提出了一种构造高斯概率密度函数的方法来模拟正演问题。
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