root-finding-algorithms
There are 0 repository under root-finding-algorithms topic.
nmltd / numerical-methods-java
Numerical Methods Using Java: For Data Science, Analysis, and Engineering https://www.amazon.com/Numerical-Methods-Using-Java-Engineering/dp/1484267966
Language:Java 6dreamchef / numerical-analysis-methods
Collection of methods for numerical analysis and scientific computing, including numerical root-finders, numerical integration, linear algebra, and data visualization. Created for APPM4600 at CU Boulder.
numerical-analysisnumerical-analysis-algorithmsnumerical-analysis-methodsnumerical-methodsscientific-computingbisection-methodconvergence-analysisconvergence-ratenumerical-solveroptimizationorder-of-convergenceroot-findingroot-finding-algorithmsroot-finding-methodsnewton-methodnewton-raphsonnewtons-methodfixed-point-iterationfixed-point-methodLanguage:Jupyter Notebook 3DhruvJ22 / Numerical-Methods
Numerical Methods
Language:Jupyter Notebook 2jadvrodrigues / EquationSolver
General-purpose equation solver (up to the 4th order) which is fast and easy to use. Unit-tested.
Language:C# 1viraj-shah18 / Fast-Polynomial-Root-Finding
This project aims to improve efficiency of root-finding methods using parallelization of GPU.
Language:CMake 1ShobhitManiar / Newton-RFA
Root finding using Newton Raphson Method
Language:C++ 0- Language:Python
ignabelitzky / roots-of-equations
Implementation and usage of numerical root-finding algorithms.
Language:Python- Language:Python
sonyafar / solve-it
Online tool for computing roots using specific starting points, precisions, and numerical methods
Language:HTMLYashIITM / Root-Finding-Algorithms
The behaviour of general root-finding algorithms is studied in numerical analysis. How-ever, for polynomials, root-finding study belongs generally to computer algebra, sincealgebraic properties of polynomials are fundamental for the most efficient algorithms. The efficiency of an algorithm may depend dramatically on the characteristics of the given functions. For example, many algorithms use the derivative of the input function,while others work on every continuous function. In general, numerical algorithms are not guaranteed to find all the roots of a function, so failing to find a root does not prove that there is no root. However, for polynomials, there are specific algorithms that use algebraic properties for certifying that no root is missed, and locating the roots in separate intervals(or disks for complex roots) that are small enough to ensure the convergence of numerical methods (typically Newton’s method) to the unique root so located.
Language:TeX
