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A remark on the metric dimension in Riemannian manifolds of constant curvature [PDF]
We compute the metric dimension of Riemannian manifolds of constant curvature. We define the edge weghited metric dimension of the geodesic graphs in Riemannian manifolds and we show that each complete geodesic graph $G=(V,E)$ embedded in a Riemannian ...
Shiva Heidarkhani Gilani +2 more
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Almost contact complex Riemannian manifolds, also known as almost contact B-metric manifolds, are, in principle, equipped with a pair of mutually associated pseudo-Riemannian metrics. Each of these metrics is specialized as a Yamabe almost soliton with a
Mancho Manev
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On the Geometry of Three-dimensional Pseudo-Riemannian Homogeneous Spaces. I [PDF]
The problem of establishing links between the curvature and the topological structure of a manifold is one of the important problems of geometry. In general, the purpose of the research of manifolds of various types is rather complicated.
Natal’ya Pavlovna Mozhey
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In this paper, we examine torse-forming vector fields to characterize extrinsic spheres (that is, totally umbilical hypersurfaces with nonzero constant mean curvatures) in Riemannian and Lorentzian manifolds.
Norah Alshehri, Mohammed Guediri
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Low Dimensional Flat Manifolds with Some Elasses of Finsler Metric
Introduction An -dimensional Riemannian manifold is said to be flat (or locally Euclidean) if locally isometric with the Euclidean space, that is, admits a covering of coordinates neighborhoods each of which is isometric with a Euclidean domain.
Sedigheh Alavi Endrajemi +1 more
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A Geometry Preserving Kernel over Riemannian Manifolds [PDF]
- Kernel trick and projection to tangent spaces are two choices for linearizing the data points lying on Riemannian manifolds. These approaches are used to provide the prerequisites for applying standard machine learning methods on Riemannian manifolds ...
Kh. Sadatnejad +2 more
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This work exploits Riemannian manifolds to build a sequential-clustering framework able to address a wide variety of clustering tasks in dynamic multilayer (brain) networks via the information extracted from their nodal time-series.
Cong Ye +4 more
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The Proximal Gradient Method for Composite Optimization Problems on Riemannian Manifolds
In this paper, the composite optimization problem is studied on Riemannian manifolds. To tackle this problem, the proximal gradient method to solve composite optimization problems is proposed on Riemannian manifolds. Under some reasonable conditions, the
Xiaobo Li
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Seiberg-Witten Equations on Pseudo-Riemannian Spinc Manifolds With Neutral Signature
Pseudo-Riemannian spinc manifolds were introduced by Ikemakhen in [7]. In the present work we consider pseudo-Riemannian 4-manifolds with neutral signature whose structure groups are SO+(2; 2).
Değirmenci Nedim, Karapazar Şenay
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On Jacobi-Type Vector Fields on Riemannian Manifolds
In this article, we study Jacobi-type vector fields on Riemannian manifolds. A Killing vector field is a Jacobi-type vector field while the converse is not true, leading to a natural question of finding conditions under which a Jacobi-type vector field ...
Bang-Yen Chen +2 more
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