# best approximation

One of the problems in approximation theory is to determine points that minimize distances (to a given point or subset). More precisely,

Problem - Let $X$ be a metric space and $S\subseteq X$ a subset. Given $x_{0}\in X$ we want to know if there exists a point in $S$ that minimizes the distance to $x_{0}$, i.e. if there exists $y_{0}\in S$ such that

 $d(x_{0},y_{0})=\inf_{y\in S}d(x_{0},y)$

Definition - A point $y_{0}$ that the above conditions is called a best approximation of $x_{0}$ in $S$.

In general, best approximations do not exist. Thus, the problem is usually to identify classes of spaces $X$ and $S$ where the existence of best approximations can be assured.

Example : When $S$ is compact, best approximations of a given point $x_{0}\in X$ in $S$ always exist.

After one assures the existence of a best approximation, one can question about its uniqueness and how to calculate it explicitly.

Remark - There is no reason to restrict to metric spaces. The definition of best approximation can be given for pseudo-metric spaces, semimetric spaces or any other space where a suitable notion of ”distance” can be given.

Title best approximation BestApproximation 2013-03-22 17:31:23 2013-03-22 17:31:23 asteroid (17536) asteroid (17536) 4 asteroid (17536) Definition msc 41A50 optimal approximation