Convergence of remote projections onto convex sets

Abstract: Let ${C_{\alpha}}{\alpha\in \Omega}$ be a family of closed and convex sets in a Hilbert space $H$, having a nonempty intersection $C$. We consider a sequence ${x_n}$ of remote projections onto them. This means, $x_0\in H$, and $x{n+1}$ is the projection of $x_n$ onto such a set $C_{\alpha(n)}$ that the ratio of the distances from $x_n$ to this set and to any other set from the family is at least $t_n\in [0,1]$. We study properties of the weakness parameters $t_n$ and of the sets $C_\alpha$ which ensure the norm or weak convergence of the sequence ${x_n}$ to a point in $C$. We show that condition (T) is necessary and sufficient for the norm convergence of $x_n$ to a point in $C$ for any starting element and any family of closed, convex, and symmetric sets $C_\alpha$. This generalizes a result of Temlyakov who introduced (T) in the context of greedy approximation theory. We give examples explaining to what extent the symmetry condition on the sets $C_{\alpha}$ can be dropped. Condition (T) is stronger than $\sum t_n^2=\infty$ and weaker than $\sum t_n/n=\infty$. The condition $\sum t_n^2=\infty$ turns out to be necessary and sufficient for the sequence ${x_n}$ to have a partial weak limit in $C$ for any family of closed and convex sets $C_\alpha$ and any starting element.