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Steklov Mathematical Institute Seminar
December 22, 2011 16:00, Moscow, Steklov Mathematical Institute of RAS, Conference Hall (8 Gubkina)

The uniqueness theorem for analytic functions. Statistical approach

I. A. Ibragimov
 Video records: Flash Video 333.1 Mb Flash Video 2,026.2 Mb MP4 333.1 Mb

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Abstract: An analytic function $f$ is fully determined by its values at any arbitrary small domain $D$. The problem of determination of the analytic function $f$ outside $D$ is an ill-posed problem, and small errors in the determination $f$ in $D$ may give rise to great errors of the determination $f$ outside $D$.
In this talk we consider the following problem. An entire function $f$ is observed in a small noise on a set $D$. How far from $D$ one can determine $f$ with small errors? A simple variant of the problem is the following one. A function $f$ is observed on an interval $[a;b]$ in the additive Gaussian noise of intensity $\varepsilon$. For example, the observation
$$X(t)=\int_0^tf(u) du+\varepsilon w(t), \qquad w(a)=0,$$
$w(t)$ is a Wiener process. It is supposed that $f$ belongs to an a priori known set of entire functions whose order of growth is at most $\rho$. It turns out that the the consistent estimation of $f$ is possible on the distances of the order $(\ln(\varepsilon^{-1}))^{1/\rho}$ and is impossible on the distances of larger order. The same results can be proved for other variants of similar problems.

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