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We show that perturbing ill-posed differential equations with (potentially very) smooth random processes can restore well-posedness -- even if the perturbation is (potentially much) more regular than the drift component of the solution. The…

Probability · Mathematics 2024-09-25 Máté Gerencsér

We present a perturbation method for determining the moment stability of linear ordinary differential equations with parametric forcing by colored noise. In particular, the forcing arises from passing white noise through an $n$th order…

Mathematical Physics · Physics 2013-01-11 Timothy Blass , L. A. Romero

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work,…

Information Theory · Computer Science 2017-01-11 Mohamed Suliman , Tarig Ballal , Tareq Y. Al-Naffouri

In this paper we construct a new type of noise of fractional nature that has a strong regularizing effect on differential equations. We consider an equation with this noise with a highly irregular coefficient. We employ a new method to…

Functional Analysis · Mathematics 2018-06-26 Oussama Amine , David Baños , Frank Proske

We present the derivation of the normalization constant for the perturbation matrix method recently proposed. The method is tested on the problem of a binary waveguide array for which an exact and an approximate solution are known. In our…

Optics · Physics 2018-04-04 B. M. Villegas-Martínez , H. M. Moya-Cessa , F. Soto-Eguibar

A regularization algorithm allowing random noise in derivatives and inexact function values is proposed for computing approximate local critical points of any order for smooth unconstrained optimization problems. For an objective function…

Optimization and Control · Mathematics 2021-04-07 S. Bellavia , G. Gurioli , B. Morini , Ph. L. Toint

Regularization is a well studied problem in the context of neural networks. It is usually used to improve the generalization performance when the number of input samples is relatively small or heavily contaminated with noise. The…

Artificial Intelligence · Computer Science 2011-04-19 Salah Rifai , Xavier Glorot , Yoshua Bengio , Pascal Vincent

A method is suggested for treating those complicated physical problems for which exact solutions are not known but a few approximation terms of a calculational algorithm can be derived. The method permits one to answer the following rather…

High Energy Physics - Phenomenology · Physics 2009-10-31 V. I. Yukalov , E. P. Yukalova

We develop new perturbation techniques for conducting convergence analysis of various first-order algorithms for a class of nonsmooth optimization problems. We consider the iteration scheme of an algorithm to construct a perturbed…

Optimization and Control · Mathematics 2018-10-25 Xiangfeng Wang , Jane Ye , Xiaoming Yuan , Shangzhi Zeng , Jin Zhang

A proper formulation in the perturbative renormalization group method is presented to deduce amplitude equations. The formulation makes it possible not only avoiding a serious difficulty in the previous reduction to amplitude equations by…

patt-sol · Physics 2009-10-30 Ken-ichi Matsuba , Kazuhiro Nozaki

We propose and analyze a perturbative regularization method to approximate quadratic optimization problems with finite-dimensional degeneracy. The original problem is first approximated by a regularized problem depending on a small positive…

Numerical Analysis · Mathematics 2026-03-16 C. G. Gebhardt , I. Romero

In this paper, we introduce the new optimal perturbation iteration method based on the perturbation iteration algorithms for the approximate solutions of nonlinear differential equations of many types. The proposed method is illustrated by…

Numerical Analysis · Mathematics 2016-09-21 Sinan Deniz , Necdet Bildik

Existence and uniqueness of solutions to the stochastic heat equation with multiplicative spatial noise is studied. In the spirit of pathwise regularization by noise, we show that a perturbation by a sufficiently irregular continuous path…

Probability · Mathematics 2021-01-05 Rémi Catellier , Fabian A. Harang

In this paper we investigate an adaptive discretization strategy for ill-posed linear prob- lems combined with a regularization from a class of semiiterative methods. We show that such a discretization approach in combination with a…

Numerical Analysis · Mathematics 2014-07-22 Wolfgang Erb , Evgeniya V. Semenova

Discrete inverse problems correspond to solving a system of equations in a stable way with respect to noise in the data. A typical approach to enforce uniqueness and select a meaningful solution is to introduce a regularizer. While for most…

Optimization and Control · Mathematics 2022-04-22 Cristian Vega , Cesare Molinari , Lorenzo Rosasco , Silvia Villa

Numerical solving differential equations with fractional derivatives requires elimination of the singularity which is inherent in the standard definition of fractional derivatives. The method of integration by parts to eliminate this…

Numerical Analysis · Mathematics 2022-01-26 Pavel B. Dubovski , Jeffrey A. Slepoi

Perturbation or error bounds of functions have been of great interest for a long time. If the functions are differentiable, then the mean value theorem and Taylor's theorem come handy for this purpose. While the former is useful in…

Functional Analysis · Mathematics 2017-04-04 Priyanka Grover

Accurate calculation of the motion of a compact object in a background spacetime induced by a supermassive black hole is required for the future detection of such binary systems by the gravitational-wave detector LISA. Reaching the desired…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Eran Rosenthal

A new perturbation and continuation method is presented for computing and analyzing stellarator equilibria. The method is formally derived from a series expansion about the equilibrium condition $F \equiv J \times B - \nabla p = 0$, and an…

Plasma Physics · Physics 2023-04-05 Rory Conlin , Daniel W. Dudt , Dario Panici , Egemen Kolemen

Analytic perturbation theory for matrices and operators is an immensely useful mathematical technique. Most elementary introductions to this method have their background in the physics literature, and quantum mechanics in particular. In…

Spectral Theory · Mathematics 2022-04-26 Bassam Bamieh
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