Results 71 to 80 of about 3,785 (249)

Three Solutions for Inequalities Dirichlet Problem Driven by p(x)-Laplacian-Like

Abstract and Applied Analysis, 2013
A class of nonlinear elliptic problems driven by p(x)-Laplacian-like with a nonsmooth locally Lipschitz potential was considered. Applying the version of a nonsmooth three-critical-point theorem, existence of three solutions of the problem is proved.
Zhou Qing-Mei, Ge Bin
doaj   +1 more source

Multiple solutions to a class of inclusion problems with operator involving p(x)-Laplacian

Electronic Journal of Qualitative Theory of Differential Equations, 2013
In this paper, we prove the existence of at least two nontrivial solutions for a nonlinear elliptic problem involving p(x)-Laplacian-like operator and nonsmooth potentials.
Qing-Mei Zhou
doaj   +1 more source

On the convergence of solutions of globally modified magnetohydrodynamics equations with locally Lipschitz delays terms

, 2022
Existence and uniqueness of strong solutions for the three dimensional system of globally modified magnetohydrodynamics equations with locally Lipschitz delays terms are established in this article.
Deugoue, G., Djoko, J.K., Fouape, A.C.
core  

Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations

Quality and Reliability Engineering International, EarlyView.
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim, Huadong Mo, Hemanshu Pota, Daoyi Dong   +3 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

Homoclinic solutions for a differential inclusion system involving the p(t)-Laplacian

Advances in Nonlinear Analysis, 2022
The aim of this article is to study nonlinear problem driven by the p(t)p\left(t)-Laplacian with nonsmooth potential. We establish the existence of homoclinic solutions by using variational principle for locally Lipschitz functions and the properties of ...
Cheng Jun, Chen Peng, Zhang Limin
doaj   +1 more source

Lipschitz maps with prescribed local Lipschitz constants

Let $Γ$ be a closed subset of a complete Riemannian manifold $M$ of dimension $\geq 2$, let $f: M \to N$ be a Lipschitz map to a complete Riemannian manifold $N$, and let $ψ$ be a continuous function which dominates the local Lipschitz constant of $f$. We construct a Lipschitz map which agress with $f$ on $Γ$ and whose local Lipschitz constant is $ψ$.
Backus, Aidan, Ze-An, Ng
openaire   +2 more sources

Surjection and inversion for locally Lipschitz maps between Banach spaces

, 2019
We study the global invertibility of non-smooth, locally Lipschitz maps between infinite-dimensional Banach spaces, using a kind of Palais-Smale condition.
Gutú, Olivia, Jaramillo Aguado, Jesús Ángel   +1 more
core   +1 more source

Numerical methods for backward stochastic differential equations of quadratic and locally Lipschitz type [PDF]

, 2013
Der Fokus dieser Dissertation liegt darauf, effiziente numerische Methode für ungekoppelte lokal Lipschitz-stetige und quadratische stochastische Vorwärts-Rückwärtsdifferenzialgleichungen (BSDE) mit Endbedingungen von schwacher Regularität zu entwickeln.
Turkedjiev, Plamen
core   +1 more source

Vertical Deformation Mapping: Steering Optimiser Toward Flat Minima

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Standard deep learning optimisation is typically conducted on shape‐fixed loss surfaces. However, shape‐fixed loss surfaces may impede optimisers from reaching flat regions closely associated with strong generalisation. In this work, we propose a new paradigm named deformation mapping to deform the loss surface during optimisation.
Liangming Chen, Longbang Wang, Man‐Fai Leung, Jianfeng Li, Long Jin   +4 more
wiley   +1 more source