Results 81 to 90 of about 3,827,469 (279)
PID‐Like Robust Control of Non‐Minimum Phase Robotic Manipulators
ABSTRACT This paper proposes an output‐feedback tracking controller for non‐minimum phase nonlinear systems with unknown uncertainties and external disturbances, where not all states are measurable, and the zero dynamics are unstable. The approach combines a backstepping‐based stabilizing state‐feedback law with a cascade extended high‐gain observer ...
Mohammad Al Saaideh +2 more
wiley +1 more source
Convergence rate of rational spline histopolation
The convergence rate of histopolation on arbitrary nonuniform mesh with linear/linear rational splines of class C1 is studied. Established convergence rate depends on Lipschitz smoothness class of the function to histopolate.
Malle Fischer, Peeter Oja
doaj +1 more source
Embedding generalized Wiener classes into Lipschitz spaces [PDF]
Summary: In this note, we give a necessary and sufficient condition for emedding the classes \(\Lambda BV^{(p_n\uparrow p)}\) into the generalized Lipschitz spaces \(H_q^{\omega}\) \((1 \leqslant q < p \leqslant \infty)\).
Moazami Goodarzi, Milad +2 more
openaire +1 more source
Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
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
On the Moduli of Lipschitz Homology Classes
Abstract We define a type of modulus $$\operatorname {dMod}_p$$ dMod p for Lipschitz surfaces based on $$L^p$$
Ilmari Kangasniemi, Eden Prywes
openaire +3 more sources
SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
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
On Metric Choice in Dimension Reduction for Fréchet Regression
Summary Fréchet regression is becoming a mainstay in modern data analysis for analysing non‐traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data.
Abdul‐Nasah Soale +3 more
wiley +1 more source
A Comparative Review of Specification Tests for Diffusion Models
Summary Diffusion models play an essential role in modelling continuous‐time stochastic processes in the financial field. Therefore, several proposals have been developed in the last decades to test the specification of stochastic differential equations.
A. López‐Pérez +3 more
wiley +1 more source
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
ABSTRACT Aim(s) To explore the feasibility and acceptability of acoustic monitoring and real‐time recommendations for stress detection and management (i.e., smarthealth intervention). Design This qualitative study used a framework of acceptability for healthcare interventions.
Eunjung Ko +9 more
wiley +1 more source

