arXiv · 2104.09573
On planar sampling with Gaussian kernel in spaces of bandlimited functions
Abstract
Let $I=(a,b)\times(c,d)\subset {\mathbb R}_{+}^2$ be an index set and let $\{G_{\alpha}(x) \}_{\alpha \in I}$ be a collection of Gaussian functions, i.e. $G_{\alpha}(x) = \exp(-\alpha_1 x_1^2 - \alpha_2 x_2^2)$, where $\alpha = (\alpha_1, \alpha_2) \in I, \, x = (x_1, x_2) \in {\mathbb R}^2$. We present a complete description of the uniformly discrete sets $\Lambda \subset {\mathbb R}^2$ such that every bandlimited signal $f$ admits a stable reconstruction from the samples $\{f \ast G_{\alpha} (\lambda)\}_{\lambda \in \Lambda}$.
Explore related subjects
Keep this discovery
Ilya Zlotnikov. 2021-04-19. On planar sampling with Gaussian kernel in spaces of bandlimited functions. https://doi.org/10.1007/s00041-022-09948-0
Cite the original work for its findings. Save a collection to share your selection of sources.