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Related papers: Derivations on almost complex manifolds

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We present a compact formula for the derivative of a 3-D rotation matrix with respect to its exponential coordinates. A geometric interpretation of the resulting expression is provided, as well as its agreement with other less-compact but…

Computer Vision and Pattern Recognition · Computer Science 2017-11-10 Guillermo Gallego , Anthony Yezzi

We give the extension formulae on almost complex manifolds and give decompositions of the extension formulae. As applications, we study $(n,0)$-forms, the $(n,0)$-Dolbeault cohomology group and $(n,q)$-forms on almost complex manifolds.

Differential Geometry · Mathematics 2020-03-17 Jixiang Fu , Haisheng Liu

We consider the approximation of manifold-valued functions by embedding the manifold into a higher dimensional space, applying a vector-valued approximation operator and projecting the resulting vector back to the manifold. It is well known…

Numerical Analysis · Mathematics 2022-10-24 Ralf Hielscher , Laura Lippert

In this paper we consider the approximation of a function by its interpolating multilinear spline and the approximation of its derivatives by the derivatives of the corresponding spline. We derive formulas for the uniform approximation…

Numerical Analysis · Mathematics 2013-08-27 Ryan Anderson , Yuliya Babenko , Tetiana Leskevych

In our recent publication [1] we presented an exponential series approximation suitable for highly accurate computation of the complex error function in a rapid algorithm. In this Short Communication we describe how a simplified…

Numerical Analysis · Mathematics 2012-05-09 S. M. Abrarov , B. M. Quine

A unified explicit form for difference formulas to approximate the fractional and classical derivatives is presented. The formula gives finite difference approximations for any classical derivatives with a desired order of accuracy at nodal…

Numerical Analysis · Mathematics 2021-05-28 W. A. Gunarathna , H. M. Nasir , W. B. Daundasekera

Simple derivations, at a level appropriate for an undergraduate computational physics course, of the most popular methods for finding the minimum of a function of many variables are presented in a unified manner in the context of a general…

Computational Physics · Physics 2007-05-23 R. A. Hyman , Bridget Doporcyk , John Tetzlaff

Finite differences have been widely used in mathematical theory as well as in scientific and engineering computations. These concepts are constantly mentioned in calculus. Most frequently-used difference formulas provide excellent…

Numerical Analysis · Mathematics 2010-06-09 Brian Jain , Andrew D. Sheng

A simple theory of the covariant derivatives, deformed derivatives and relative covariant derivatives of extensor fields is present using algebraic and analytical tools developed in previous papers. Several important formulas are derived.

Mathematical Physics · Physics 2007-05-23 V. V. Fernandez , A. M. Moya , E. Notte-Cuello , W. A. Rodrigues

We construct explicit easily implementable polynomial approximations of sufficiently high accuracy for locally constant functions on the union of disjoint segments. This problem has important applications in several areas of numerical…

Functional Analysis · Mathematics 2023-11-29 Yuri Malykhin , Konstantin Ryutin

We give an algorithm to compute the series expansion for the inverse of a given function. The algorithm is extremely easy to implement and gives the first $N$ terms of the series. We show several examples of its application in calculating…

Classical Analysis and ODEs · Mathematics 2007-05-23 Diego Dominici

Approximate solutions to functional evolution equations are constructed through a combination of series and conjugation methods, and relative errors are estimated. The methods are illustrated, both analytically and numerically, by…

Mathematical Physics · Physics 2015-03-19 Thomas Curtright , Xiang Jin , Cosmas Zachos

In the paper, a method of describing the outer derivations of the group algebra of a finitely presentable group is given. The description of derivations is given in terms of characters of the groupoid of the adjoint action of the group.

Rings and Algebras · Mathematics 2017-08-18 A. A. Arutyunov , A. S. Mishchenko , A. I. Shtern

We derive a variational model to fit a composite B\'ezier curve to a set of data points on a Riemannian manifold. The resulting curve is obtained in such a way that its mean squared acceleration is minimal in addition to remaining close the…

Numerical Analysis · Mathematics 2018-12-10 Ronny Bergmann , Pierre-Yves Gousenbourger

Diffusive representations of fractional derivatives have proven to be useful tools in the construction of fast and memory efficient numerical methods for solving fractional differential equations. A common challenge in many of the known…

Numerical Analysis · Mathematics 2022-04-11 Kai Diethelm

Many interesting functions arising in applications map into Riemannian manifolds. We present an algorithm, using the manifold exponential and logarithm, for approximating such functions. Our approach extends approximation techniques for…

Numerical Analysis · Mathematics 2026-01-27 Simon Jacobsson , Raf Vandebril , Joeri van der Veken , Nick Vannieuwenhoven

Variational Bayes is a popular method for approximate inference but its derivation can be cumbersome. To simplify the process, we give a 3-step recipe to identify the posterior form by explicitly looking for linearity with respect to…

Machine Learning · Computer Science 2023-07-11 Mohammad Emtiyaz Khan

We discuss a short-time existence theorem of solutions to the initial value problem for a third order dispersive flow for closed curves into a compact almost Hermitian manifold. Our equations geometrically generalize a physical model…

Analysis of PDEs · Mathematics 2008-07-30 Hiroyuki Chihara , Eiji Onodera

Gradient-based techniques are becoming increasingly critical in quantitative fields, notably in statistics and computer science. The utility of these techniques, however, ultimately depends on how efficiently we can evaluate the derivatives…

Computation · Statistics 2020-02-04 Michael Betancourt , Charles C. Margossian , Vianey Leos-Barajas

This paper describes a novel method to approximate the polynomial coefficients of regression functions, with particular interest on multi-dimensional classification. The derivation is simple, and offers a fast, robust classification…

Machine Learning · Statistics 2012-03-27 Péter Kövesárki
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