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arXiv 0912.2872math.CAmath.OC
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具有不确定数据的线性常微分方程边值问题的参数估计

Estimation of parameters of boundary value problems for linear ordinary differential equations with uncertain data

Olexandr Nakonechnyi, Yury Podlipenko, Yury Shestopalov

摘要:

本文利用加性随机噪声扰动下的观测值作为两点边值问题解的线性变换,构造了一阶线性常微分方程解的线性泛函的最优估计.这里假设方程的右端和边界数据以及观测值中随机噪声的统计特性是未知的,并且属于相应函数空间中的某些给定集合。当最优估计被定义为关于观测值的线性估计时,这就有必要引入估计问题的极小极大陈述,使得在上述集合上的估计的均方误差的最大值达到极小值。这种估计称为极小化极大估计。我们证明极小化极大估计是通过某些特殊类型的微分方程组的解来表示的。考虑了具有一般边界条件的n阶线性微分方程边值问题解的类似估计问题。本文还详细讨论了在方程右端和边界数据未知的不完全数据下的极小极大估计方法,并给出了相应的极小化极大估计的表示.在所有的情况下,估计误差被确定。

英文摘要:

In this paper we construct optimal, in certain sense, estimates of values of linear functionals on solutions to two-point boundary value problems (BVPs) for systems of linear first-order ordinary differential equations from observations which are linear transformations of the same solutions perturbed by additive random noises. It is assumed here that right-hand sides of equations and boundary data as well as statistical characteristics of random noises in observations are not known and belong to certain given sets in corresponding functional spaces. This leads to the necessity of introducing minimax statement of an estimation problem when optimal estimates are defined as linear, with respect to observations, estimates for which the maximum of mean square error of estimation taken over the above-mentioned sets attains minimal value. Such estimates are called minimax estimates. We establish that the minimax estimates are expressed via solutions of some systems of differential equations of special type. Similar estimation problems for solutions of BVPs for linear differential equations of order n with general boundary conditions are considered. We also elaborate minimax estimation methods under incomplete data of unknown right-hand sides of equations and boundary data and obtain representations for the corresponding minimax estimates. In all the cases estimation errors are determined.

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