Results 81 to 90 of about 4,279 (247)

Characterization of Lipschitz Spaces via Commutators of Fractional Maximal Function on the $p$-Adic Variable Exponent Lebesgue Spaces

Comptes Rendus. Mathématique
In this paper, the main aim is to give some characterizations of the boundedness of the maximal or nonlinear commutator of the $p$-adic fractional maximal operator $ \mathcal{M}_{\alpha }^{p}$ with the symbols belong to the $p$-adic Lipschitz spaces in ...
Wu, Jianglong, Chang, Yunpeng
doaj   +1 more source

Fault‐Tolerant Fuzzy Boundary Control for Nonlinear Distributed Parameter Systems Under Limited Measurements and Markovian Failures

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This paper proposes a boundary control method for nonlinear distributed parameter systems (DPSs) with limited boundary measurements (BMs), as typically encountered in networked cyber‐physical processes with spatially distributed dynamics such as thermal and biomedical diffusion systems.
Yanlin Li, Kaibo Shi, Yue Yu, Xiangkun Wang, Ming Zhu, Xiao Cai   +5 more
wiley   +1 more source

Bi-Lipschitz decomposition of Lipschitz functions into a metric space

Revista Matemática Iberoamericana, 2009
We prove a quantitative version of the following statement. Given a Lipschitz function f from the k-dimensional unit cube into a general metric space, one can be decomposed f
openaire   +5 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, Florine Hartwig, Josua Sassen, Sergio Conti, Mirela Ben‐Chen, Martin Rumpf   +5 more
wiley   +1 more source

A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces

International Statistical Review, EarlyView.
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, Bernardo Nipoti, Emilio Porcu, Philip White   +3 more
wiley   +1 more source

A note on generalised information criteria for structured sparse models

International Statistical Review, EarlyView.
Summary We propose a generalised information criteria ( gic) that accounts for sparsity pattern in the model. We obtain both asymptotic and nonasymptotic results for model selection. Moreover, we show that the gic is useful for selecting the regularisation parameter in regularised m$$ m $$ estimation in high‐dimensional scenarios.
Eduardo Fonseca Mendes, Gabriel Jardim Pereira Pinto   +1 more
wiley   +1 more source

Classification of Lipschitz Derivatives in Terms of Semicontinuity and the Baire Limit Functions

Annales Mathematicae Silesianae
We introduce the generalized notion of semicontinuity of a function defined on a topological space and derive the useful classification of the so-called Lipschitz derivatives of functions defined on a metric space.
Maslyuchenko Oleksandr V., Wójcicki Ziemowit M.   +1 more
doaj   +1 more source

Global optimization of Lipschitz functions

, 2017
The goal of the paper is to design sequential strategies which lead to efficient optimization of an unknown function under the only assumption that it has a finite Lipschitz constant. We first identify sufficient conditions for the consistency of generic sequential algorithms and formulate the expected minimax rate for their performance.
Cédric Malherbe, Nicolas Vayatis
openaire   +3 more sources

Detecting Relevant Deviations From the White Noise Assumption for Non‐Stationary Time Series

Journal of Time Series Analysis, EarlyView.
ABSTRACT We consider the problem of detecting deviations from a white noise assumption in time series. Our approach differs from the numerous methods proposed for this purpose with respect to two aspects. First, we allow for non‐stationary time series. Second, we address the problem that a white noise test is usually not performed because one believes ...
Patrick Bastian
wiley   +1 more source

Adaptive Estimation for Weakly Dependent Functional Times Series

Journal of Time Series Analysis, EarlyView.
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro, Valentin Patilea, Myriam Vimond   +2 more
wiley   +1 more source