The problem of recovering coefficients in a diffusion equation is one of the basic inverse problems. Perhaps the most important term is the one that couples the length and time scales and is often referred to as {\it the\/} diffusion coefficient $a$ in $u_t - \nabla(a\nabla u) = f$. In this paper we seek the unknown $a$ assuming that $a=a(u)$ depends only on the value of the solution at a given point. Such diffusion models are the basic of a wide range of physical phenomena such as nonlinear heat conduction, chemical mixing and population dynamics. We shall look at two types of overposed data in order to effect recovery of $a(u)$: the value of a time trace $u(x_0,t)$ for some fixed point $x_0$ on the boundary of the region $\Omega$; or the value of $u$ on an interior curve $\Sigma$ lying within $\Omega$. As examples, these might represent a temperature measurement on the boundary or a census of the population in some subset of $\Omega$ taken at a fixed time $T>0$. In the latter case we shall show a uniqueness result that leads to a constructive method for recovery of $a$. Indeed, for both types of measured data we shall show reconstructions based on the iterative algorithms developed in the paper.
翻译:在扩散方程式中恢复系数的问题是一个基本反向问题。 也许最重要的一个术语是,在时间和时间尺度上对齐,通常被称作 $_t_t-\nabla(a\bla u) = f$的传播系数 = f$。在本文中,我们寻求一个未知的美元,假设美元=a(u)美元仅取决于某一点的解决方案值。这种传播模型是非线性热导、化学混合和人口动态等一系列广泛物理现象的基础。我们应查看两类过量数据,以便实现美元(u) 美元(nabla)(a\\ nbla u) = f美元(f美元) = f美元。在本文中,假设美元=a=a(a) 美元(a) =a(u) =a(u) 美元) =(u) =美元(o) 美元(u),或美元(b) 美元=(ogega美元) 。例如,这可能代表对边界的温度测量,或(a) 美元) 美元(a) 美元(a) 美元) 美元(a (a (a) ro ro) 美元) 美元) =(ro) 美元) 的恢复结果,我们将显示(a (a (a (a) = 美元) =