Differential equations

Adomian decomposition method

The Adomian decomposition method (ADM) is a semi-analytical method for solving ordinary and partial nonlinear differential equations. The method was developed from the 1970s to the 1990s by George Adomian, chair of the Center for Applied Mathematics at the University of Georgia. It is further extensible to stochastic systems by using the Ito integral. The aim of this method is towards a unified theory for the solution of partial differential equations (PDE); an aim which has been superseded by the more general theory of the homotopy analysis method. The crucial aspect of the method is employment of the "Adomian polynomials" which allow for solution convergence of the nonlinear portion of the equation, without simply linearizing the system. These polynomials mathematically generalize to a Maclaurin series about an arbitrary external parameter; which gives the solution method more flexibility than direct Taylor series expansion. (Wikipedia).

Adomian decomposition method
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LU Decomposition Using Elementary Matrices

This video explains how find the LU Decomposition of a square matrix using elementary matrices. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com

From playlist Matrix Equations

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Solve a System of Linear Equations Using LU Decomposition

This video explains how to use LU Decomposition to solve a system of linear equations. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com

From playlist Matrix Equations

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How to integrate by partial fractions

Free ebook http://bookboon.com/en/learn-calculus-2-on-your-mobile-device-ebook How to integrate by the method of partial fraction decomposition. In algebra, the partial fraction decomposition or partial fraction expansion of a rational fraction (that is a fraction such that the numerator

From playlist A second course in university calculus.

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Jean Ecalle: Taming the coloured multizetas

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From playlist Dynamical Systems and Ordinary Differential Equations

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Ex: Setting Up Partial Fraction Decomposition

This video provides several examples of how to set up the fractions in order to perform partial fraction decomposition. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com

From playlist Performing Partial Fraction Decomposition

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Integration Using Partial Fraction Decomposition Part 1

This video shows how partial fraction decomposition can be used to simplify and integral. This video only shows linear factors. Part 1 of 2 Site: http://mathispower4u.com

From playlist Integration Using Partial Fractions

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Computational Physics Lecture 11, LU Decomposition and Matrix Inversion

In this lecture, we discuss the LU decomposition method for systems of linear algebraic equations. We then describe how to calculate the inverse of a matrix using this method. We also introduce the concept of the matrix condition number. Finally, we describe a simple iterative method for i

From playlist Nazarbayev: PHYS 270 - Computational Physics with Ernazar Ab

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Using Elimination to Solve Systems

👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e

From playlist Solve a System of Equations Using Elimination | Medium

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LU Decomposition - Shortcut Method

This video explains how to find the LU Decomposition of a square matrix using a shortcut involving the opposite of multipliers used when performing row operations. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com

From playlist Matrix Equations

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Empirical Mode Decomposition (1D, univariate approach)

Introduction to the Empirical Mode Decomposition - EMD - (one-dimensional, univariate version), which is a data decomposition method for non-linear and non-stationary data. This video covers the main features of the EMD and the working principle of the algorithm. The EMD is briefly compar

From playlist Summer of Math Exposition Youtube Videos

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Martin J. Gander: Multigrid and Domain Decomposition: Similarities and Differences

Both multigrid and domain decomposition methods are so called optimal solvers for Laplace type problems, but how do they compare? I will start by showing in what sense these methods are optimal for the Laplace equation, which will reveal that while both multigrid and domain decomposition a

From playlist Numerical Analysis and Scientific Computing

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Partial Fraction Decomposition (Part 2)

Partial fraction decomposition is when a rational expression is written as the sum of simpler fractions. This video is part 2 - it will explain how to complete the proper decomposition form to find the partial fractions of a rational function. Partial fractions are very helpful in Calculu

From playlist Pre-Calculus / Trigonometry

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Virginie Ehrlacher - Multi-center decomposition of molecular densities: a mathematical perspective

Recorded 04 May 2022. Virginie Ehrlacher of the École Nationale des Ponts-et-Chaussées presents "Multi-center decomposition of molecular densities: a mathematical perspective" at IPAM's Large-Scale Certified Numerical Methods in Quantum Mechanics Workshop. Abstract: The aim of this talk is

From playlist 2022 Large-Scale Certified Numerical Methods in Quantum Mechanics

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6. Singular Value Decomposition; Iterative Solutions of Linear Equations

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From playlist MIT 10.34 Numerical Methods Applied to Chemical Engineering, Fall 2015

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Mod-01 Lec-18 L U decomposition

Elementary Numerical Analysis by Prof. Rekha P. Kulkarni,Department of Mathematics,IIT Bombay.For more details on NPTEL visit http://nptel.ac.in

From playlist NPTEL: Elementary Numerical Analysis | CosmoLearning Mathematics

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Deep Learning Lecture 7.3 - TICA, TCCA and time-autoencoders

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From playlist Deep Learning Lecture

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Jean Kossaifi: "Efficient Tensor Representation for Deep Learning with TensorLy and PyTorch"

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From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021

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Lecture 9 | Convex Optimization II (Stanford)

Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd concludes his lecture on primal and dual decomposition methods. This course introduces topics such as subgradient, cutting-plane, and ellipsoid method

From playlist Lecture Collection | Convex Optimization

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Solving a system of equations with infinite many solutions

👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e

From playlist Solve a System of Equations Using Elimination | Medium

Related pages

Differential equation | Order of approximation | Boundary layer | Blasius boundary layer | Polynomial | Maclaurin series | Elliptic partial differential equation | Maple (software) | Homotopy analysis method | Taylor series | Initial value problem | Integral equation | Hilbert space | Navier–Stokes equations | Padé approximant | Weak convergence (Hilbert space) | Cauchy problem | Fredholm integral equation | Partial differential equation