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A new method for solving systems of linear algebraic equations of a special type arising in solving problems of image reconstruction has been proposed. This method, due to a certain symmetry of the matrix and the choice of the voxel…

Numerical Analysis · Mathematics 2019-08-30 A. A. Alikhanov , A. M. Apekov , Z. A. Kokov , A. O. Belyaev , L. A. Khamukova

We present the iterative classical point symmetry analysis of a shallow water wave equation in $2+1$ dimensions and that of its corresponding nonisospectral, two component Lax pair. A few reductions arise and are identified with celebrate…

Exactly Solvable and Integrable Systems · Physics 2015-10-19 P. G. Estévez , J. D. Lejarreta , C. Sardón

When using a finite difference method to solve an initial--boundary--value problem, the truncation error is often of lower order at a few grid points near boundaries than in the interior. Normal mode analysis is a powerful tool to analyze…

Numerical Analysis · Mathematics 2018-08-23 Siyang Wang , Anna Nissen , Gunilla Kreiss

Manifold hypothesis states that data points in high-dimensional space actually lie in close vicinity of a manifold of much lower dimension. In many cases this hypothesis was empirically verified and used to enhance unsupervised and…

Some aspects of the connection between differential geometry and multidimensional soliton equations are discussed.

Differential Geometry · Mathematics 2007-05-23 R. Myrzakulov

Recently, there has been much interest in spectral approaches to learning manifolds---so-called kernel eigenmap methods. These methods have had some successes, but their applicability is limited because they are not robust to noise. To…

Machine Learning · Computer Science 2011-12-30 Byron Boots , Geoffrey J. Gordon

The techniques and analysis presented in this thesis provide new methods to solve optimization problems posed on Riemannian manifolds. These methods are applied to the subspace tracking problem found in adaptive signal processing and…

Optimization and Control · Mathematics 2013-05-09 Steven Thomas Smith

Recently, there has been much interest in spectral approaches to learning manifolds---so-called kernel eigenmap methods. These methods have had some successes, but their applicability is limited because they are not robust to noise. To…

Machine Learning · Computer Science 2012-06-22 Byron Boots , Geoff Gordon

The classical Lie method is applied to a nonisospectral problem associated with a system of partial differential equations in 2+1 dimensions (Maccari A, J. Math. Phys. 39, (1998), 6547-6551). Identification of the classical Lie symmetries…

Exactly Solvable and Integrable Systems · Physics 2011-09-27 P. G. Estevez , M. L. Gandarias , J. de Lucas

When analyzing parametric statistical models, a useful approach consists in modeling geometrically the parameter space. However, even for very simple and commonly used hierarchical models like statistical mixtures or stochastic deep neural…

Machine Learning · Computer Science 2021-12-08 Pascal Mattia Esser , Frank Nielsen

We present a refinement of the Spectral Method by incorporating an optimization method into it and generalize it to two space dimensions. We then apply this Refined Spectral Method as an extremely accurate technique for finding the bound…

Mathematical Physics · Physics 2007-05-23 P. Pedram , M. Mirzaei , S. S. Gousheh

The purpose of this note is to survey a methodology to solve systems of polynomial equations and inequalities. The techniques we discuss use the algebra of multivariate polynomials with coefficients over a field to create large-scale linear…

Optimization and Control · Mathematics 2011-12-08 Jesus A. De Loera , Peter N. Malkin , Pablo A. Parrilo

We use the methods of group theory to reduce the equations of motion of the $CP^{1}$ model in (2+1) dimensions to sets of two coupled ordinary differential equations. We decouple and solve many of these equations in terms of elementary…

High Energy Physics - Theory · Physics 2009-10-28 A. M. Grundland , P. Winternitz , W. J. Zakrzewski

A connection between differential geometry and soliton equations is discussed

Differential Geometry · Mathematics 2007-05-23 R. Myrzakulov

Manifold learning based methods have been widely used for non-linear dimensionality reduction (NLDR). However, in many practical settings, the need to process streaming data is a challenge for such methods, owing to the high computational…

Machine Learning · Statistics 2018-03-20 Suchismit Mahapatra , Varun Chandola

The invariant subspace method is refined to present more unity and more diversity of exact solutions to evolution equations. The key idea is to take subspaces of solutions to linear ordinary differential equations as invariant subspaces…

Exactly Solvable and Integrable Systems · Physics 2015-06-04 Wen-Xiu Ma

This article addresses the study of the complex version of the modified Korteweg-de Vries equation using two different approaches. Firstly, the singular manifold method is applied in order to obtain the associated spectral problem, binary…

Exactly Solvable and Integrable Systems · Physics 2024-02-28 Paz Albares , Pilar G. Estévez , Alejandro González-Parra , Paula del Olmo

In this paper, using the similarity method, we construct particular solutions with singularities for degenerate high-order equations. The considered equations have singularities of the first and second kind. Particular solutions are…

Analysis of PDEs · Mathematics 2020-05-06 B. Yu. Irgashev

An algorithmic method to exploit a general class of infinitesimal symmetries for reducing stochastic differential equations is presented and a natural definition of reconstruction, inspired by the classical reconstruction by quadratures, is…

Probability · Mathematics 2020-08-04 Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

We give an overview of invariants of algebraic singularities over perfect fields. We then show how they lead to a synthetic proof of embedded resolution of singularities of 2-dimensional schemes.

Algebraic Geometry · Mathematics 2011-10-04 Angélica Benito , Orlando E. Villamayor