Results 91 to 100 of about 65,484 (270)
On non-separable components of hyperspaces with the Hausdorff metric [PDF]
Let $(X,d)$ be a connected non compact metric space. Suppose the metric$d$ convex and such that every closed bounded subset of $X$ is compact. Let $F(X)$ bethe space of nonvoid closed subsets of $X$ with the Hausdorff distance associated to $d$.We prove ...
R. Cauty
doaj
Topographic Gromov-Hausdorff quantum Hypertopology for Quantum Proper Metric Spaces
We construct a topology on the class of pointed proper quantum metric spaces which generalizes the topology of the Gromov-Hausdorff distance on proper metric spaces, and the topology of the dual propinquity on Leibniz quantum compact metric spaces.
Latremoliere, Frederic
core
Some bounds related to the 2‐adic Littlewood conjecture
Abstract For every irrational real α$\alpha$, let M(α)=supn⩾1an(α)$M(\alpha) = \sup _{n\geqslant 1} a_n(\alpha)$ denote the largest partial quotient in its continued fraction expansion (or ∞$\infty$, if unbounded). The 2‐adic Littlewood conjecture (2LC) can be stated as follows: There exists no irrational α$\alpha$ such that M(2kα)$M(2^k \alpha)$ is ...
Dinis Vitorino, Ingrid Vukusic
wiley +1 more source
Semiclassical inequalities for Dirichlet and Neumann Laplacians on convex domains
Abstract We are interested in inequalities that bound the Riesz means of the eigenvalues of the Dirichlet and Neumann Laplacians in terms of their semiclassical counterpart. We show that the classical inequalities of Berezin–Li–Yau and Kröger, valid for Riesz exponents γ≥1$\gamma \ge 1$, extend to certain values γ<1$\gamma <1$, provided the underlying ...
Rupert L. Frank, Simon Larson
wiley +1 more source
Recovering metric from full ordinal information
Given a geodesic space (E, d), we show that full ordinal knowledge on the metric d-i.e. knowledge of the function D d : (w, x, y, z) $\rightarrow$ 1 d(w,x)$\le$d(y,z) , determines uniquely-up to a constant factor-the metric d.
Gouic, Thibaut Le
core
Realizations of Gromov-Hausdorff Distance
6 ...
Ivanov, Alexander +2 more
openaire +2 more sources
ABSTRACT Purpose This study aims to develop an automated framework for operator‐independent assessment of cardiac ventricular function from highly accelerated images. Methods We introduce a deep learning framework that generates reliable ventricular volumetric parameters and strain measures from fully sampled and retrospectively accelerated MR images ...
Aya Ghoul +7 more
wiley +1 more source
In this paper, an image denoising algorithm is presented based on the two-dimensional variational mode decomposition (2D-VMD) and the Hausdorff distance (HD).
Hongyu Gao +4 more
doaj +1 more source
Computation of the Hausdorff Distance between Two Compact Convex Sets. [PDF]
Lange K.
europepmc +1 more source
Calculating Gromov-Hausdorff Distance by means of Borsuk Number [PDF]
Alexander Ivanov +1 more
openalex +1 more source

