Numerical Methods for Partial Differential Equations
Numerical solution techniques for partial differential equations, covering Poisson's equation, eigenvalue equations, heat conduction equation, and wave equation with implementation approaches
Numerical Methods for Two-Dimensional Hyperbolic and Parabolic Partial Differential Equations in MATLAB
Numerical Solution Methods for 2D Hyperbolic and Parabolic PDEs in MATLAB Environment with Code Implementation Insights
Numerical Methods for Partial Differential Equations
Implementation of numerical methods for partial differential equations in MATLAB environment, featuring practical MATLAB programs for PDE numerical experiments
Numerical Methods for Partial Differential Equations Package
A comprehensive software package for numerical solutions of partial differential equations, featuring implementations of Lax-Friedrichs, Lax-Wendroff, and upwind schemes with configurable parameters and extensible architecture
Numerical Solution Methods for the Reynolds Equation
Numerical solution approach for the Reynolds equation using matrix formulation and linear algebra techniques
Fourth-Order Runge-Kutta Numerical Method for Solving Coupled Rate Equations
Implementation of Fourth-Order Runge-Kutta Numerical Method for Solving Systems of Coupled Differential Equations
Fourth-Order Runge-Kutta Method for Numerical Solution of First-Order Differential Equations
The fourth-order Runge-Kutta method provides a numerical solution for first-order differential equations with customizable iteration steps and precision, making it ideal for computational method beginners. Implementation typically involves calculating four slope estimates per step to achieve high accuracy.
Numerical Methods for Partial Differential Equations
MATLAB Algorithm Collections - Numerical Solutions for Partial Differential Equations with Implementation Details
MATLAB Implementation of the EM Algorithm
This program implements the Expectation-Maximization (EM) algorithm, providing a numerical solution for parameter estimation using maximum likelihood techniques.
Numerical Solution Example 1.1.3 from Sun Zhizhong's "Numerical Methods for Partial Differential Equations"
Implementation of Example 1.1.3 using compact difference scheme to solve ordinary differential equation boundary value problems, featuring efficient discretization and matrix-based solutions.