Results 11 to 20 of about 6,501 (223)

Application of Nyström method to a Fredholm integral equation describing induction heating

open access: yesEPJ Web of Conferences, 2015
An induction heating problem can be described by a Fredholm Integral Equation of the second kind. The equation is used to compute the eddy current of density. One method for solving such an equation is the Nyström method. It is based on the approximation
Rak Josef
doaj   +2 more sources

An adaptive optimized Nyström method for second‐order IVPs [PDF]

open access: yesMathematical methods in the applied sciences, 2022
[EN]This research work deals with the development, analysis, and implementation of an adaptive optimized one-step Nyström method for solving second-order initial value problems of ODEs and time-dependent partial differential equations.
Mufutau Ajani Rufai   +5 more
core   +2 more sources

Solving linear Fredholm integro-differential equation by Nyström method

open access: yesJournal of Applied Mathematics and Computational Mechanics, 2021
The study of the solution’s existence and uniqueness for the linear integro-differential Fredholm equation and the application of the Nyström method to approximate the solution is what we will present in this paper.
Boutheina Tair   +3 more
doaj   +2 more sources

Nystrom Method for Accurate and Scalable Implicit Differentiation [PDF]

open access: yesInternational Conference on Artificial Intelligence and Statistics, 2023
The essential difficulty of gradient-based bilevel optimization using implicit differentiation is to estimate the inverse Hessian vector product with respect to neural network parameters.
Ryuichiro Hataya, M. Yamada
semanticscholar   +1 more source

Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nyström method [PDF]

open access: yesarXiv.org, 2023
Asymmetric data naturally exist in real life, such as directed graphs. Different from the common kernel methods requiring Mercer kernels, this paper tackles the asymmetric kernel-based learning problem.
Qinghua Tao   +3 more
semanticscholar   +1 more source

On numerical solution of Fredholm and Hammerstein integral equations via Nyström method and Gaussian quadrature rules for splines

open access: yesApplied Numerical Mathematics, 2022
Nyström method is a standard numerical technique to solve Fredholm integral equations of the second kind where the integration of the kernel is approximated using a quadrature formula.
D. Barrera   +3 more
semanticscholar   +1 more source

Analysis of a Monte-Carlo Nystrom Method

open access: yesSIAM Journal on Numerical Analysis, 2022
. This paper considers a Monte-Carlo Nystrom method for solving integral equa- 3 tions of the second kind, whereby the values ( z ( y i )) 1 ≤ i ≤ N of the solution z at a set of N random 4 and independent points ( y i ) 1 ≤ i ≤ N are approximated by the
F. Feppon, H. Ammari
semanticscholar   +1 more source

Kernel Adaptive Filtering Prediction Algorithm of Chaotic Time Series [PDF]

open access: yesZhengzhou Daxue xuebao. Gongxue ban, 2023
In practical environment, chaotic time series often contain a lot of noise and outliers. Because of these interference factors, the prediction performance of the kernel adaptive filter based on the second-order similarity measure could decrease ...
LIU Qiang   +3 more
doaj   +1 more source

Combining Nyström Methods for a Fast Solution of Fredholm Integral Equations of the Second Kind

open access: yesMathematics, 2021
In this paper, we propose a suitable combination of two different Nyström methods, both using the zeros of the same sequence of Jacobi polynomials, in order to approximate the solution of Fredholm integral equations on [−1,1].
Domenico Mezzanotte   +2 more
doaj   +1 more source

Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method

open access: yesNeural Information Processing Systems, 2020
The Column Subset Selection Problem (CSSP) and the Nystrom method are among the leading tools for constructing interpretable low-rank approximations of large datasets by selecting a small but representative set of features or instances.
Michal Derezinski   +2 more
semanticscholar   +1 more source

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