Numerical analysis | Iterative methods
In computational mathematics, an iterative method is a mathematical procedure that uses an initial value to generate a sequence of improving approximate solutions for a class of problems, in which the n-th approximation is derived from the previous ones. A specific implementation of an iterative method, including the termination criteria, is an algorithm of the iterative method. An iterative method is called convergent if the corresponding sequence converges for given initial approximations. A mathematically rigorous convergence analysis of an iterative method is usually performed; however, heuristic-based iterative methods are also common. In contrast, direct methods attempt to solve the problem by a finite sequence of operations. In the absence of rounding errors, direct methods would deliver an exact solution (for example, solving a linear system of equations by Gaussian elimination). Iterative methods are often the only choice for nonlinear equations. However, iterative methods are often useful even for linear problems involving many variables (sometimes on the order of millions), where direct methods would be prohibitively expensive (and in some cases impossible) even with the best available computing power. (Wikipedia).
Comparing Iterative and Recursive Factorial Functions
Comparing iterative and recursive factorial functions
From playlist Computer Science
Euler’s method - How to use it?
► My Differential Equations course: https://www.kristakingmath.com/differential-equations-course Euler’s method is a numerical method that you can use to approximate the solution to an initial value problem with a differential equation that can’t be solved using a more traditional method,
From playlist Differential Equations
Jacobi, Gauss-Seidel and SOR Methods | Lecture 66 | Numerical Methods for Engineers
Iterative methods for solving the discrete Laplace equation. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my channel: http://www.youtube.com/user/jchasnov?
From playlist Numerical Methods for Engineers
B01 An introduction to numerical methods
Most differential equations cannot be solved by the analytical techniques that we have learned up until now. I these cases, we can approximate a solution by a set of points, by using a variety of numerical methods. The first of these is Euler's method.
From playlist A Second Course in Differential Equations
Newton's Method | Lecture 14 | Numerical Methods for Engineers
Derivation of Newton's method for root finding. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my channel: http://www.youtube.com/user/jchasnov?sub_confirmat
From playlist Numerical Methods for Engineers
Solve a System of Equations Using Elimination
👉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 | Hard
Python Tutorial: Iterators and Iterables - What Are They and How Do They Work?
In this Python Programming Tutorial, we will be learning about iterators and iterables. There is a lot of confusion around these terms and exactly what they mean. We're also going to learn how to make an object ourselves that is both an iterable and an iterator. This video isn't only about
From playlist Python Tutorials
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
Martin Gander: On the invention of iterative methods for linear systems
HYBRID EVENT Recorded during the meeting "1Numerical Methods and Scientific Computing" the November 9, 2021 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians on
From playlist Numerical Analysis and Scientific Computing
Victorita Dolean: An introduction to domain decomposition methods - lecture 2
HYBRID EVENT Recorded during the meeting "Domain Decomposition for Optimal Control Problems" the September 06, 2022 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematici
From playlist Jean-Morlet Chair - Gander/Hubert
34th Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk
For more information and past webinars, visit our website: https://sites.google.com/view/oneworldimagine Date: October 20, 2021, 10:00am Eastern Time Zone (US & Canada) / 2:00pm GMT Speaker: Per Christian Hansen, DTU Title: Convergence and Non-Convergence of Algebraic Iterative Reconstr
From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series
Wegstein Method for finding roots, accelerating fixed point iteration, and inducing convergence in fixed point iteration. Explained examples and discussion of order as well as how to compute q. Example code: https://github.com/osveliz/numerical-veliz Chapters 0:00 Intro 0:22 Wegstein's Me
From playlist Root Finding
Aaron Sidford: Introduction to interior point methods for discrete optimization, lecture I
Over the past decade interior point methods (IPMs) have played a pivotal role in mul- tiple algorithmic advances. IPMs have been leveraged to obtain improved running times for solving a growing list of both continuous and combinatorial optimization problems including maximum flow, bipartit
From playlist Summer School on modern directions in discrete optimization
Iterators In Python | Python Iterators Explained | Python Tutorial For Beginners | Simplilearn
🔥Artificial Intelligence Engineer Program (Discount Coupon: YTBE15): https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=IteratorsInPython-pMgHS_DbE4I&utm_medium=Descriptionff&utm_source=youtube 🔥Professional Certificate Program In AI And Machine Learning: https://w
From playlist Python For Beginners 🔥[2022 Updated]
Lec 12 | MIT Finite Element Procedures for Solids and Structures, Linear Analysis
Lecture 12: Solution methods for frequencies and mode shapes Instructor: Klaus-Jürgen Bathe View the complete course: http://ocw.mit.edu/RES2-002S10 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT Linear Finite Element Analysis
Differential Equations | Exact Equations and Integrating Factors Example 2
We give an example of converting a non-exact differential equation into an exact equation. We use this to solve the differential equation.
From playlist Numerical Methods for Differential Equations