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Pseudospectral collocation methods and finite difference methods have been used for approximating an important family of soliton like solutions of the mKdV equation. These solutions present a structural instability which make difficult to…

Numerical Analysis · Mathematics 2011-09-29 Carlos Gorria , Miguel A. Alejo , Luis Vega

In this note it is shown that two key results on transcendental singularities for meromorphic functions of finite lower order have refinements which hold under the weaker hypothesis that the logarithmic derivative has finite lower order.

Complex Variables · Mathematics 2018-07-26 J. K. Langley

Recently, there has been significant progress in the development of distributed first order methods. (At least) two different types of methods, designed from very different perspectives, have been proposed that achieve both exact and linear…

Information Theory · Computer Science 2017-12-27 Dusan Jakovetic

High-order spatial discretisations and full discretisations of parabolic partial differential equations on evolving surfaces are studied. We prove convergence of the high-order evolving surface finite element method, by showing high-order…

Numerical Analysis · Mathematics 2016-06-24 Balázs Kovács

For a discrete function $f\left( x\right) $ on a discrete set, the finite difference can be either forward and backward. If $f\left( x\right) $ is a sum of two such functions $f\left( x\right) =f_{1}\left( x\right) +f_{2}\left( x\right) $,…

Statistical Mechanics · Physics 2022-05-06 Q. H. Liu

In this comment, we raise serious concerns over the derivation of the rate of convergence of fractional steepest descent algorithm in Fractional Adaptive Learning (FAL) approach presented in `Fractional Extreme Value Adaptive Training…

Optimization and Control · Mathematics 2019-02-13 Abdul Wahab , Shujaat Khan

In [Kopteva, Math. Comp., 2014] a counterexample of an anisotropic triangulation was given on which the exact solution has a second-order error of linear interpolation, while the computed solution obtained using linear finite elements is…

Numerical Analysis · Mathematics 2019-05-22 Natalia Kopteva

We show a new, elementary and geometric proof of the classical Alexandrov theorem about the second order differentiability of convex functions. We also show new proofs of recent results about Lusin approximation of convex functions and…

Classical Analysis and ODEs · Mathematics 2023-08-02 Daniel Azagra , Anthony Cappello , Piotr Hajłasz

The authors show that the round-off error can break the consistency which is the premise of using the difference equation to replace the original differential equations. We therefore proposed a theoretical approach to investigate this…

Numerical Analysis · Mathematics 2010-06-23 Wang Pengfei , Li Jianping

Gallagher's theorem describes the multiplicative diophantine approximation rate of a typical vector. We establish a fully-inhomogeneous version of Gallagher's theorem, a diophantine fibre refinement, and a sharp and unexpected threshold for…

Number Theory · Mathematics 2023-08-25 Sam Chow , Niclas Technau

There is a deformation of the ordinary differential calculus which leads from the continuum to a lattice (and induces a corresponding deformation of physical theories). We recall some of its features and relate it to a general framework of…

High Energy Physics - Theory · Physics 2007-05-23 A. Dimakis , F. M"uller-Hoissen

The paper is devoted to the development of control procedures with a guide for conflict-controlled dynamical systems described by ordinary fractional differential equations with the Caputo derivative of an order $\alpha \in (0, 1).$ For the…

Optimization and Control · Mathematics 2019-01-10 Mikhail Gomoyunov

We present a novel approach of discretizing variable coefficient diffusion operators in the context of meshfree generalized finite difference methods. Our ansatz uses properties of derived operators and combines the discrete Laplace…

Numerical Analysis · Mathematics 2024-06-21 Heinrich Kraus , Jörg Kuhnert , Pratik Suchde

This paper introduces a second-order differential inclusion for unconstrained convex optimization. In continuous level, solution existence in proper sense is obtained and exponential decay of a novel Lyapunov function along with the…

Optimization and Control · Mathematics 2022-03-01 Hao Luo

A fully discrete Lagrangian scheme for solving a family of fourth order equations numerically is presented. The discretization is based on the equation's underlying gradient flow structure w.r.t. the $L^2$-Wasserstein distance, and adapts…

Numerical Analysis · Mathematics 2015-01-23 Horst Osberger

The purpose of this work is the development and determination of higher-order continuum-like kinematic measures which characterize discrete kinematic data obtained from experimental measurement (e.g., digital image correlation) or kinematic…

Materials Science · Physics 2022-06-22 Mohammad Khorrami , Jaber R. Mianroodi , Bob Svendsen

In this work, we revisit a classical incremental implementation of the primal-descent dual-ascent gradient method used for the solution of equality constrained optimization problems. We provide a short proof that establishes the linear…

Optimization and Control · Mathematics 2020-01-17 Sulaiman A. Alghunaim , Ali H. Sayed

Explicit numerical methods based on Lax-Friedrichs and Leap-Frog finite difference approximations are constructed to find the numerical solution of the first-order hyperbolic partial differential equation with point-wise delay or advance,…

Numerical Analysis · Mathematics 2010-12-07 Paramjeet Singh , Kapil K. Sharma

We consider the numerical construction of minimal Lagrangian graphs, which is related to recent applications in materials science, molecular engineering, and theoretical physics. It is known that this problem can be formulated as an…

Numerical Analysis · Mathematics 2021-07-01 Brittany Froese Hamfeldt , Jacob Lesniewski

Convolutional sparse representations are a form of sparse representation with a dictionary that has a structure that is equivalent to convolution with a set of linear filters. While effective algorithms have recently been developed for the…

Machine Learning · Computer Science 2018-09-06 Cristina Garcia-Cardona , Brendt Wohlberg