Results 81 to 90 of about 119,767,946 (229)
Solution sets of differential equations in abstract spaces
Aim of the monograph is to analyze the structure of the solution set of a differential equations in the more general case of abstract topological (infinite dimensional) spaces. Specifically, we consider both the spaces with a paucity of useful properties,
ZECCA P. +3 more
core +1 more source
In this paper, the author introduces the Neural-ODE Hybrid Block Method, which serves as a direct solution for solving higher-order ODEs. Many single and multi-step methods employed in numerical approximations lose their stability when applied in the ...
V. Murugesh +7 more
doaj +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
This article is a status report on the anholonomic frame and connection deformation method, AFCDM, for constructing generic off-diagonal exact and parametric solutions in general relativity, GR, relativistic geometric flows and modified gravity theories,
Laurenţiu Bubuianu +5 more
doaj +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
In the study of Volterra integral equations of convolution type defined on the semi-axis with the Fredholm operator in the main part and the operator-valued kernel K = K(t) in Banach spaces we ordinarily solved the problem of constructing a generalized K(
S.S. Orlov
doaj
MU-LSM: latent spectral model based on multi-scale fusion and UNet
For partial differential equations (PDE), neural operators can learn the mapping of input and output functions in infinite dimensional Spaces by introducing kernel functions into linear transformations.
Jingjian Chen +4 more
doaj +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
In this paper, we establish several interpolation inequalities in the weighted Lebesgue spaces and Morrey spaces. By using the classical Calderón–Zygmund decomposition with respect to ω (a weight function), we prove that L p ( ω ) ∩ BMO ( R n ) ⊂ L q ( ω
Hua Wang
doaj +1 more source

