Results 81 to 90 of about 2,172 (181)

Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver

open access: yesInternational Journal for Numerical Methods in Fluids, Volume 98, Issue 7, Page 804-839, July 2026.
A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
wiley   +1 more source

Boundary Feedback Control Design for Classes of Mixed-Type Partial Differential Equations [PDF]

open access: yes, 2019
The work in this dissertation summarizes some advancement in the theory of boundary controller design for coupled partial differential equations (PDEs), including a new interpretation of designing bilateral boundary controllers as equivalent coupled PDEs
Chen, Stephen
core  

Design of unknown input observers for nonlinear systems with full and partial information

open access: yes, 2016
The problem of designing Unknown Input Observers (UIOs) for nonlinear systems is approached in this paper, in the cases of full and partial information. In the former, it is shown that the construction hinges upon the solution of a system of first-order ...
Cristofaro, A   +7 more
core   +1 more source

Prediction-based control of linear input-delay system subject to state-dependent state delay – Application to suppression of mechanical vibrations in drilling

open access: yes, 2016
International audienceIn this paper, we consider linear dynamics subject to a distributed state-dependent delay and a pointwise input-delay. We propose a prediction-based controller which exponentially stabilizes the plant. The controller design is based
Bresch-Pietri, Delphine   +1 more
core   +1 more source

Multi‐Targeting Ligands as Prospective Therapeutics for Alzheimer's Disease, a Prevalent Neurodegenerative Disorder: Mechanistic Insights, Emerging Targets and Drug Discovery Campaigns

open access: yesMedicinal Research Reviews, Volume 46, Issue 4, Page 1173-1229, July 2026.
ABSTRACT Alzheimer's disease (AD) is a debilitating neurodegenerative condition characterized by progressive cognitive impairment, memory deterioration, and neuronal dysfunction. Its complex pathophysiology involves multiple interlinked processes, including amyloid‐β (Aβ) aggregation, tau hyperphosphorylation, oxidative stress, neuroinflammation ...
Amandeep Thakur   +6 more
wiley   +1 more source

Stabilization of Pulses by Diffusion

open access: yes, 2007
Stationary and traveling pulses appear generically in the dynamics generated by nonlinear partial differential equations (PDEs) of evolution type.
A. Doelman
core  

Stability of a Fully Discrete Local Discontinuous Galerkin Method for the Generalized Benjamin–Ono Equation

open access: yesNumerical Methods for Partial Differential Equations, Volume 42, Issue 4, July 2026.
ABSTRACT The main purpose of this paper is to design a fully discrete local discontinuous Galerkin (LDG) scheme for the generalized Benjamin–Ono equation. First, we prove the L2$$ {L}^2 $$‐stability for the proposed semi‐discrete LDG scheme and obtained a suboptimal order of convergence for power nonlinear flux.
Mukul Dwivedi, Tanmay Sarkar
wiley   +1 more source

AutomataGPT: Transformer‐Based Forecasting and Ruleset Inference for Two‐Dimensional Cellular Automata

open access: yesAdvanced Science, Volume 13, Issue 33, 15 June 2026.
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich   +2 more
wiley   +1 more source

DATA-DRIVEN SINGLE-/MULTI-DOMAIN SPECTRAL METHODS FOR STOCHASTIC FRACTIONAL PDES

open access: yes, 2018
Fractional derivatives are integro-differential convolution type operators with power law kernels, which seamlessly generalize the notion of standard integer order differentiation to their fractional counter parts.
Kharazmi, Ehsan
core   +1 more source

Physical Implementation of Optical Material‐Based Neural Networks Processing Enabled by Long‐Persistent Luminescence

open access: yesAdvanced Science, Volume 13, Issue 31, 4 June 2026.
This study reports on the physical implementation of optical material‐based neural processing using long‐persistent luminescence as memory‐retention and nonlinear optical material. The system performs optical‐domain preprocessing with opto‐electronic interfaces for stimulus delivery and readout, enabling real‐time demonstrations including Pong gameplay
Sangwon Wi, Yunsang Lee
wiley   +1 more source

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