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Explicit Numerical Methods to solve Differential Equation

version 1.0.0.0 (981 Bytes) by Sathyanarayan Rao
Here , I compare Euler, Runge-Kutta and Adam-Bashforth methods to integrate a simple function.

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Updated 03 Jan 2016

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A simple sinusoidal function is integrated using different well known explicit schemes and error is compared at the end.

Cite As

Sathyanarayan Rao (2020). Explicit Numerical Methods to solve Differential Equation (https://www.mathworks.com/matlabcentral/fileexchange/54726-explicit-numerical-methods-to-solve-differential-equation), MATLAB Central File Exchange. Retrieved .

Comments and Ratings (1)

A generalized framework called MaxPol has been recently published and made available here
https://www.mathworks.com/matlabcentral/fileexchange/63294-maxpol-smoothing-and-differentiation-package

MaxPol provides a framework to design variety of numerical differentiation kernels with properties like:
(1) Cutoff (lowpass) design with no side-lob artifacts (for noise-robust case)
(2) Arbitrary order of differentiation
(3) Arbitrary polynomial accuracy
(4) Derivative matrix design
(5) 2D Derivative Kernels with Steering moments
(6) Intuitive examples in Signal and Image processing

Updates

1.0.0.0

Added a function to be integrated

MATLAB Release Compatibility
Created with R2010a
Compatible with any release
Platform Compatibility
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