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Applied-Numerical-Methods

Provides knowledge about Applied Numerical Methods in vit (Vellore Institute of Technology) VIT BHOPAL UNIVERSITY

#Overview

(1)

Algebraic, Transcendental and linear system of equations

Introduction to Direct and Iterative methods – (Fixed point) Iteration

method - order and condition of convergence - Secant and Newton- Raphson methods for simple roots – Rates of convergence - Gauss- Elimination – Thomas Algorithm for tridiagonal linear system of

equations - Gauss-Seidel iteration method - Diagonal dominance and convergence of Gauss-Seidel iteration method

(2)

Interpolation

Finite difference operators: Forward, Backward, Central, Average, Shift and Differential – Relation between these difference operators – Interpolation - Newton’s forward and backward Interpolations -– Lagrange Interpolation - Newton’s Divided Difference Interpolation - Cubic spline interpolation for a tabulated function with equally spaced data

(3)

Numerical Differentiation and Integration

Derivatives using Newton’s Forward and Backward interpolations – Newton-Cotes Quadrature rule - Trapezoidal rule, Simpson’s 1/3 and 3/8 rules – Gaussian Quadrature rule - Two point and three point Gauss-Legendre quadrature rules – composite quadrature rules - Romberg method

(4)

Numerical Solution of Ordinary Differential Equations

First order initial value problems - Taylor’s Series method - Euler’s method - Modified Euler’s method - Runge–Kutta method of fourth order - Adams-Bashforth predictor-corrector method - Finite difference method for second order boundary value problems

(5)

Numerical Solution of Partial Differential Equations

Classification of second order linear partial differential equations – Finite difference method – Explicit and Implicit methods - Schmidt and Crank-Nicolson methods for 1-D heat equation – Explicit method for 1-D wave equation – Liebmann’s iteration method for 2-D Laplace and Poisson equations

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  • Open Source Licenced
  • For Educational Purpose

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