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The present work deals with an improved back-propagation algorithm based on Gauss-Newton numerical optimization method for fast convergence. The steepest descent method is used for the back-propagation. The algorithm is tested using various…

Artificial Intelligence · Computer Science 2012-06-21 Sudarshan Nandy , Partha Pratim Sarkar , Achintya Das

We present a novel numerical method, called {\tt Jacobi-predictor-corrector approach}, for the numerical solution of fractional ordinary differential equations based on the polynomial interpolation and the Gauss-Lobatto quadrature w.r.t.…

Numerical Analysis · Mathematics 2014-01-30 Lijing Zhao , Weihua Deng

In this paper, we explain the convergence speed of different iteration schemes with the fluid diffusion view when solving a linear fixed point problem. This interpretation allows one to better understand why power iteration or Jacobi…

Numerical Analysis · Computer Science 2013-04-08 Dohy Hong

Estimating the number of components is a fundamental challenge in unsupervised learning, particularly when dealing with high-dimensional data with many components or severely imbalanced component sizes. This paper addresses this challenge…

Machine Learning · Statistics 2026-04-22 Huan Qing

We discuss a recursive family of iterative methods for the numerical approximation of roots of nonlinear functions in one variable. These methods are based on Newton-Cotes closed quadrature rules. We prove that when a quadrature rule with…

Numerical Analysis · Mathematics 2014-09-10 Mario M. Graça , Pedro M. Lima

We present improved algorithms for fast calculation of the inverse square root for single-precision floating-point numbers. The algorithms are much more accurate than the famous fast inverse square root algorithm and have the same or…

Numerical Analysis · Computer Science 2018-02-22 Cezary J. Walczyk , Leonid V. Moroz , Jan L. Cieśliński

We provide explicit expressions for quadrature rules on the space of $C^1$ cubic splines with non-uniform, symmetrically stretched knot sequences. The quadrature nodes and weights are derived via an explicit recursion that avoids an…

Numerical Analysis · Mathematics 2014-10-28 Rachid Ait-Haddou , Michael Bartoň , Victor Manuel Calo

We develop efficient numerical integration methods for computing an integral whose integrand is a product of a smooth function and the Gaussian function with a small standard deviation. Traditional numerical integration methods applied to…

Numerical Analysis · Mathematics 2018-04-12 Yunyun Ma , Yuesheng Xu

In parallel simulation, convergence and parallelism are often seen as inherently conflicting objectives. Improved parallelism typically entails lighter local computation and weaker coupling, which unavoidably slow the global convergence.…

Graphics · Computer Science 2025-06-10 Lei Lan , Zixuan Lu , Chun Yuan , Weiwei Xu , Hao Su , Huamin Wang , Chenfanfu Jiang , Yin Yang

Currently, mass matrices are computed by means of sufficiently accurate numerical integration schemes. Two-point and nine-point (Gauss) quadrature remain frequently used. We derive an exact, easy to implement integration rule for six-node…

Numerical Analysis · Mathematics 2014-12-23 Eli Hanukah

We consider quadrature formulas based on interpolation using the basis functions $1/(1+t_kx)$ $(k=1,2,3,\ldots)$ on $[-1,1]$, where $t_k$ are parameters on the interval $(-1,1)$. We investigate two types of quadratures: quadrature formulas…

Classical Analysis and ODEs · Mathematics 2025-10-20 Walter Van Assche , Ingrid Vanherwegen

Based upon the fast computation of the coefficients of the interpolation polynomials at Chebyshev-type points by FFT, DCT and IDST, respectively, together with the efficient evaluation of the modified moments by forwards recursions or by…

Numerical Analysis · Mathematics 2013-12-16 Shuhaung Xiang , Guo He , Haiyong Wang

Gaussian graphical models are widely used to infer dependence structures. Bayesian methods are appealing to quantify uncertainty associated with structural learning, i.e., the plausibility of conditional independence statements given the…

Methodology · Statistics 2025-11-05 Deborah Sulem , Jack Jewson , David Rossell

Gau{\ss} cubature (multidimensional numerical integration) rules are the natural generalisation of the 1D Gau{\ss} rules. They are optimal in the sense that they exactly integrate polynomials of as high a degree as possible for a particular…

Numerical Analysis · Mathematics 2025-10-20 David De Wit

A novel recurrence formula for moments with respect to M\"{u}ntz-Legendre polynomials is proposed and applied to construct a numerical method for solving generalized Gauss quadratures with power function weight for M\"{u}ntz systems. These…

Numerical Analysis · Mathematics 2023-10-23 Huaijin Wang , Chuanju Xu

In this technical note we show how to reach a remarkable speed up when solving elliptic partial differential equations with finite differences thanks to the joint use of the Chebyshev-Jacobi method with high order discretizations and its…

Numerical Analysis · Mathematics 2017-05-02 J. E. Adsuara , M. A. Aloy , P. Cerdá-Durán , I. Cordero-Carrión

Recently Ahmadi et al. (2021) and Tagliaferro (2022) proposed some iterative methods for the numerical solution of linear systems which, under the classical hypothesis of strict diagonal dominance, typically converge faster than the Jacobi…

Numerical Analysis · Mathematics 2024-04-11 Paolo Novati , Fulvio Tagliaferro , Marino Zennaro

This paper addresses the challenge of solving large-scale nonlinear equations with H\"older continuous Jacobians. We introduce a novel Incremental Gauss--Newton (IGN) method within explicit superlinear convergence rate, which outperforms…

Optimization and Control · Mathematics 2024-07-04 Zhiling Zhou , Zhuanghua Liu , Chengchang Liu , Luo Luo

A scheme for approximating the kernel $w$ of the fractional $\alpha$-integral by a linear combination of exponentials is proposed and studied. The scheme is based on the application of a composite Gauss-Jacobi quadrature rule to an integral…

Numerical Analysis · Mathematics 2018-10-12 Daniel Baffet

A new type of quadrature is developed. The Gaussian quadrature, for a given measure, finds optimal values of a function's argument (nodes) and the corresponding weights. In contrast, the Lebesgue quadrature developed in this paper, finds…

Numerical Analysis · Mathematics 2020-02-25 Vladislav Gennadievich Malyshkin