Results 51 to 60 of about 35,710 (245)
A class of second-order geometric quasilinear hyperbolic PDEs and their application in imaging science [PDF]
, 2019 In this paper, we study damped second-order dynamics, which are quasilinear hyperbolic partial differential equations (PDEs). This is inspired by the recent development of second-order damping systems for accelerating energy decay of gradient flows.
Dong, Guozhi +2 more
core +3 more sources
International Transactions on Electrical Energy Systems, 2023 In this paper, the development and application of the radial basis function-finite difference (RBF-FD) method and the RBF-finite difference time domain (RBF-FDTD) method for solving electrical transient problems in power systems that are defined by the ...
Duc-Quang Vu +2 more
doaj +1 more source
Probabilistic numerical methods for PDE-constrained Bayesian inverse problems [PDF]
AIP Conference Proceedings, 2017 This paper develops meshless methods for probabilistically describing discretisation error in the numerical solution of partial differential equations. This construction enables the solution of Bayesian inverse problems while accounting for the impact of the discretisation of the forward problem.
Cockayne, J +3 more
openaire +5 more sources
Are physiological oscillations physiological?
The Journal of Physiology, EarlyView., 2023 Abstract figure legend Mechanisms and functions of physiological oscillations. Abstract Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function.
Lingyun (Ivy) Xiong, Alan Garfinkel
wiley +1 more source
Gradient Statistics-Based Multi-Objective Optimization in Physics-Informed Neural Networks
Sensors, 2023 Modeling and simulation of complex non-linear systems are essential in physics, engineering, and signal processing. Neural networks are widely regarded for such tasks due to their ability to learn complex representations from data.
Sai Karthikeya Vemuri, Joachim Denzler
doaj +1 more source
A discrete linearizability test based on multiscale analysis [PDF]
, 2010 In this paper we consider the classification of dispersive linearizable partial difference equations defined on a quad-graph by the multiple scale reduction around their harmonic solution.
Agrotis M +22 more
core +2 more sources
Semivariogram methods for modeling Whittle-Mat\'ern priors in Bayesian inverse problems
, 2020 We present a new technique, based on semivariogram methodology, for obtaining point estimates for use in prior modeling for solving Bayesian inverse problems.
Bardsley, Johnathan M. +2 more
core +1 more source
Continuous analogue to iterative optimization for PDE-constrained inverse problems [PDF]
Inverse Problems in Science and Engineering, 2018 The parameters of many physical processes are unknown and have to be inferred from experimental data. The corresponding parameter estimation problem is often solved using iterative methods such as steepest descent methods combined with trust regions. For a few problem classes also continuous analogues of iterative methods are available.
Boiger, R. +3 more
openaire +4 more sources
Axioms, 2023 We study three-dimensional potentials of the form V=U(xp+yp+zp), where U is an arbitrary function of C2-class, and p∈Z, which produces a preassigned two-parametric family of spatial regular orbits given in the solved form f(x,y,z) = c1, g(x,y,z) = c2 (c1,
Thomas Kotoulas
doaj +1 more source
A comparative study of structural similarity and regularization for joint inverse problems governed by PDEs [PDF]
Inverse Problems, 2018 Joint inversion refers to the simultaneous inference of multiple parameter fields from observations of systems governed by single or multiple forward models.
B. Crestel, G. Stadler, O. Ghattas
semanticscholar +1 more source