Results 71 to 80 of about 560,829 (251)
Orbital Stabilization of Hybrid Mechanical Systems—A Port‐Hamiltonian Approach
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT In this article, we address the problem of stabilizing hybrid periodic orbits in mechanical systems characterized by both continuous and discrete dynamics. We introduce a total energy shaping controller, formulated in the port‐Hamiltonian framework, that guarantees asymptotic orbital stability of a prescribed hybrid periodic orbit.
Thomas O'Brien +2 more
wiley +1 more source
Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley +1 more source
Characterization of Strict Convexity for Locally Lipschitz Functions
Rocky Mountain Journal of Mathematics, 2009 It is well known that a smooth function \(f: X\to\mathbb{R}\) is convex iff \(f''(x;h, h)\geq 0\) for all \(x\in X\) and all \(h\in X\). The function \(f\) is strictly convex iff \(f''(x;h,h)> 0\) for ``almost'' all \(x\in X\) and all \(h\in X\). Here \[ f''(x;u,v)= \lim_{t\to 0} \frac{\langle\nabla f(x+ tu)-\nabla f(x),v\rangle}{t}, \] where \(\nabla ...
openaire +3 more sources
SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
Computer Graphics Forum, EarlyView.We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier +5 more
wiley +1 more source
Some notes on commutators of the fractional maximal function on variable Lebesgue spaces
Journal of Inequalities and Applications, 2019 Let ...
Pu Zhang, Zengyan Si, Jianglong Wu
doaj +1 more source
Lipschitz harmonic functions on vertex-transitive graphs
, 2023 We prove that every locally finite vertex-transitive graph $G$ admits a non-constant Lipschitz harmonic function.Comment: 5 ...
Amir, Gideon +3 more
core
Progressive Convex Hull Simplification
Computer Graphics Forum, EarlyView.Abstract Convex hulls are useful as tight bounding proxies for a variety of tasks including collision detection, ray intersection, and distance computation. Unfortunately, the complexity of polyhedral convex hulls grows linearly with their input. We consider the problem of conservatively simplifying a convex hull to a specified number of half‐spaces ...
Alec Jacobson
wiley +1 more source
Multiple Solutions for a Class of Differential Inclusion System Involving the (p(x),q(x))-Laplacian
Abstract and Applied Analysis, 2012 We consider a differential inclusion system involving the (p(x),q(x))-Laplacian with Dirichlet boundary condition on a bounded domain and obtain two nontrivial solutions under appropriate hypotheses.
Bin Ge, Ji-Hong Shen
doaj +1 more source
A Characterization of bi-Lipschitz embeddable metric spaces in terms of local bi-Lipschitz embeddability [PDF]
Mathematical Research Letters, 2011 We characterize uniformly perfect, complete, doubling metric spaces which embed bi- Lipschitzly into Euclidean space. Our result applies in particular to spaces of Grushin type equipped with Carnot-Carathéodory distance. Hence we obtain the first example of a sub-Riemannian mani- fold admitting such a bi-Lipschitz embedding.
openaire +2 more sources
Compactly supported detail field for high quality neural implicit surfaces
Computer Graphics Forum, EarlyView.Abstract Neural implicit surfaces are a powerful tool for encoding a surface as the zero level set of a neural function. Trained using gradient‐descent based optimizers, these methods however suffer from a low‐frequency bias that prevents them to fit fine details of the surface.
Guillaume Coiffier, Justine Basselin
wiley +1 more source