Relevant sampling in finitely generated shift-invariant spaces

We consider random sampling in finitely generated shift-invariant spaces $V(Φ) \subset {\rm L}^2(\mathbb{R}^n)$ generated by a vector $Φ= (φ_1,\ldots,φ_r) \in {\rm L}^2(\mathbb{R}^n)^r$. Following the approach introduced by Bass and Gröchenig, we consider certain relatively compact subsets $V_{R,δ}(Φ)$ of such a space, defined in terms of a concentration inequality with respect to a cube with side lengths $R$. Under very mild assumptions on the generators, we show that for $R$ sufficiently large, taking $O(R^n log(R^{n^2/α'}))$ many random samples (taken independently uniformly distributed within $C_R$) yields a sampling set for $V_{R,δ}(Φ)$ with high probability. Here $α' \le n$ is a suitable constant.We give explicit estimates of all involved constants in terms of the generators $φ_1, \ldots, φ_r$.

No reviews yet.

No comments yet.