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We introduce a data-driven order reduction method for nonlinear control systems, drawing on recent progress in machine learning and statistical dimensionality reduction. The method rests on the assumption that the nonlinear system behaves…

Optimization and Control · Mathematics 2016-04-04 Jake Bouvrie , Boumediene Hamzi

This study is concerned with the numerical solution of a class of infinite-horizon linear regulation problems with state equality constraints and output feedback control. We propose two numerical methods to convert the optimal control…

Optimization and Control · Mathematics 2023-12-19 Kareem T. Elgindy , Hareth M. Refat

In this paper, a novel multigrid method based on Newton iteration is proposed to solve nonlinear eigenvalue problems. Instead of handling the eigenvalue $\lambda$ and eigenfunction $u$ separately, we treat the eigenpair $(\lambda, u)$ as…

Numerical Analysis · Mathematics 2024-04-30 Fei Xu , Manting Xie , Meiling Yue

In this paper, we propose a novel eigenpair-splitting method, inspired by the divide-and-conquer strategy, for solving the generalized eigenvalue problem arising from the Kohn-Sham equation. Unlike the commonly used domain decomposition…

Numerical Analysis · Mathematics 2024-11-08 Yang Kuang , Guanghui Hu

We propose a two-sided Lanczos method for the nonlinear eigenvalue problem (NEP). This two-sided approach provides approximations to both the right and left eigenvectors of the eigenvalues of interest. The method implicitly works with…

Numerical Analysis · Mathematics 2016-07-13 Sarah W. Gaaf , Elias Jarlebring

In this paper an extension of the spectral Lanczos' tau method to systems of nonlinear integro-differential equations is proposed. This extension includes (i) linearization coefficients of orthogonal polynomials products issued from…

Numerical Analysis · Mathematics 2017-02-15 P. B. Vasconcelos , J. Matos , M. S. Trindade

We generalize ideas in the recent literature and develop new ones in order to propose a general class of contour integral methods for linear convection-diffusion PDEs and in particular for those arising in finance. These methods aim to…

Numerical Analysis · Mathematics 2021-05-31 Nicola Guglielmi , Maria López-Fernández , Mattia Manucci

For nonlinear reduced-order models, especially for those with non-polynomial nonlinearities, the computational complexity still depends on the dimension of the original dynamical system. As a result, the reduced-order model loses its…

Numerical Analysis · Mathematics 2013-04-30 Zhu Wang

The eigenvalue problem plays a central role in linear algebra and its applications in control and optimization methods. In particular, many matrix decompositions rely upon computation of eigenvalue-eigenvector pairs, such as diagonal or…

Optimization and Control · Mathematics 2016-07-15 Pavel Osinenko , Grigory Devadze , Stefan Streif

Nonlinear systems and interaction forces are pervasive in many scientific fields, such as nanoscale metrology and materials science, but their accurate identification is challenging due to their complex behaviour and inaccessibility of…

Systems and Control · Electrical Eng. & Systems 2023-06-05 Eyal Baruch , Izhak Bucher

Often, polynomials or rational functions, orthogonal for a particular inner product are desired. In practical numerical algorithms these polynomials are not constructed, but instead the associated recurrence relations are computed.…

Numerical Analysis · Mathematics 2023-11-28 Marc Van Barel , Niel Van Buggenhout , Raf Vandebril

Image inpainting involves filling in damaged or missing regions of an image by utilizing information from the surrounding areas. In this paper, we investigate a highly nonlinear partial differential equation inspired by the modified…

Analysis of PDEs · Mathematics 2024-10-29 Darko Mitrovic , Andrej Novak

Contour integrals of rational functions over ${\cal M}_{0,n}$, the moduli space of $n$-punctured spheres, have recently appeared at the core of the tree-level S-matrix of massless particles in arbitrary dimensions. The contour is determined…

High Energy Physics - Theory · Physics 2016-05-25 Freddy Cachazo , Humberto Gomez

In this article, we propose two kinds of neural networks inspired by power method and inverse power method to solve linear eigenvalue problems. These neural networks share similar ideas with traditional methods, in which the differential…

Numerical Analysis · Mathematics 2023-07-18 Qihong Yang , Yangtao Deng , Yu Yang , Qiaolin He , Shiquan Zhang

Nonlinear eigenvalue equations arise naturally in quantum information theory, particularly in the variational quantification of entanglement. In this work, we present a hybrid analytical and numerical framework for evaluating the geometric…

Mathematical Physics · Physics 2025-11-17 Abrar Ahmed Naqash , Fardeen Ahmad Sofi , Mohammad Haris Khan , Sundus Abdi

This manuscript presents a new extended linear system for integral equation based techniques for solving boundary value problems on locally perturbed geometries. The new extended linear system is similar to a previously presented technique…

Numerical Analysis · Mathematics 2021-03-17 Yabin Zhang , Adrianna Gillman

We discuss a new method of integration over matrix variables based on a suitable gauge choice in which the angular variables decouple from the eigenvalues at least for a class of two-matrix models. The calculation of correlation functions…

High Energy Physics - Theory · Physics 2010-04-06 A. D'Adda

Numerical solution of nonlinear eigenvalue problems (NEPs) is frequently encountered in computational science and engineering. The applicability of most existing methods is limited by matrix structures, property of eigen-solutions, size of…

Numerical Analysis · Mathematics 2016-05-26 Jinyou Xiao , Chuanzeng Zhang , Tsung-Ming Huang , Tetsuya Sakurai

Nonlinear eigenvalue problems arise in a wide range of physical systems, in which system parameters depend on the eigenvalue. Such systems have been proposed to exhibit an extreme sensitivity of their spectra to boundary conditions, which…

Mesoscale and Nanoscale Physics · Physics 2026-04-28 Kota Otsuka , Kazuki Yokomizo

The current paper presents a new approach to multilinear dynamical systems analysis and control. The approach is based upon recent developments in tensor decompositions and a newly defined algebra of circulants. In particular, it is shown…

Machine Learning · Computer Science 2021-09-01 Randy C. Hoover , Kyle Caudle , Karen Braman