Results 21 to 30 of about 2,763,547 (281)
Decomposition of ordinary differential equations
Bulletin of Mathematical Sciences, 2017 Decompositions of linear ordinary differential equations (ode’s) into components of lower order have successfully been employed for determining their solutions. Here this approach is generalized to nonlinear ode’s. It is not based on the existence of Lie
Fritz Schwarz
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On some dynamical reconstruction problems for a nonlinear system of the second-order [PDF]
Opuscula Mathematica, 2010 The problem of reconstruction of unknown characteristics of a nonlinear system is considered. Solution algorithms stable with respect to the informational noise and computational errors are specified. These algorithms are based on the method of auxiliary
Marina Blizorukova, Vyacheslav Maksimov
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An Optimal Control Problem by a Hybrid System of Hyperbolic and Ordinary Differential Equations
Games, 2021 This paper deals with an optimal control problem for a linear system of first-order hyperbolic equations with a function on the right-hand side determined from controlled bilinear ordinary differential equations. These ordinary differential equations are
Alexander Arguchintsev +1 more
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Data-Centric Engineering, 2022 The dimension of models derived on the basis of data is commonly restricted by the number of observations, or in the context of monitored systems, sensing nodes.
Zhilu Lai +5 more
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Stiff neural ordinary differential equations [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021 Neural Ordinary Differential Equations (ODEs) are a promising approach to learn dynamical models from time-series data in science and engineering applications. This work aims at learning neural ODEs for stiff systems, which are usually raised from chemical kinetic modeling in chemical and biological systems.
Suyong Kim +4 more
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Известия высших учебных заведений. Поволжский регион: Физико-математические науки, 2020 Background. There is no problem in finding a general solution to the ordinary differential Clairaut equation. The corresponding procedure is described in details in the theory of ordinary differential equations.
L. A. Zhidova
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A method for constructing a complete bifurcation picture of a boundary value problem for nonlinear partial differential equations: application of the Kolmogorov-Arnold theorem [PDF]
Известия высших учебных заведений: Прикладная нелинейная динамикаThe purpose of this study is to develop a numerical method for bifurcation analysis of nonlinear partial differential equations, based on the reduction of partial differential equations to ordinary ones, using the Kolmogorov-Arnold theorem.
Gromov, Vasily Alexandrovich +4 more
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Optical neural ordinary differential equations
Optics Letters, 2023 Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance. However, the successive cascading of network hidden layers results in larger integrated photonic chip areas. To address this issue, we propose the optical neural ordinary differential equations (ON-ODEs) architecture that parameterizes ...
Yun Zhao +7 more
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Computability of Ordinary Differential Equations [PDF]
, 2018 In this paper we provide a brief review of several results about the computability of initial-value problems (IVPs) defined with ordinary differential equations (ODEs). We will consider a variety of settings and analyze how the computability of the IVP will be affected.
Graça, Daniel, Zhong, Ning
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Pursuit Curves and Ordinary Differential Equations
Communications, 2012 This paper deals with the differential equations which describe curves of pursuit, in which the pursuer's velocity vector always points directly towards the pursued. We use the Laplace Transform method to solve the classic problem of four mice pursuit.
Zuzana Malacka
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