Scientific Computing using Matlab Q14TWBWV1M

URI	`m2://res/Q14TWBWV1M`
Kind	course
Creators	Mani Mehra (instructor), Vivek Kumar Aggarwal (instructor)
Date	2020-08-06
Scope	in

Expressions

e1: edition

Language	en
Date	2020-08-06

m1: page, IIT Delhi Delhi Technological University (record). nptel 111102137
m2: page, 2020-08-06 (record). nptel 111102137

Contents

part 1: MATLAB
session 1: Introduction to Matlab
session 2: Plotting of Functions in Matlab
session 3: Symbolic Computation in Matlab
session 4: Functions definition in Matlab
session 5: In continuation of basics of Matlab
part 2: Module 2
session 6: In continuation of basics of Matlab (contd...)
session 7: Floating point representation of a number
session 8: Errors arithmetic
session 9: Iterative method for solving nonlinear equations
session 10: Bisection method for solving nonlinear equations
part 3: Module 3
session 11: Order of Convergence of an Iterative Method
session 12: Regula-Falsi and Secant Method for Solving Nonlinear Equations
session 13: Raphson method for solving nonlinear equations
session 14: Newton-Raphson Method for Solving Nonlinear System of Equations
session 15: Matlab Code for Fixed Point Iteration Method
part 4: Module 4
session 16: Matlab Code for Newton-Raphson and Regula-Falsi Method
session 17: Matlab Code for Newton Method for Solving System of Equations
session 18: Linear System of Equations
session 19: Linear System of Equations (contd.)
session 20: Gauss Elimination Method for solving Linear System of Equation
session 21: Matlab Code for Gauss Elimination Method
part 5: Module 5
session 22: LU Decomposition Method for Solving Linear System of Equations
session 23: LU Decomposition Method for Solving Linear System of Equations (contd.)
session 24: Iterative Method for Solving Linear System of Equations
session 25: Iterative Method for Solving Linear System of Equations (contd.)
session 26: Matlab Code for Gauss Jacobi Method
session 27: Matlab Code for Gauss Seidel Method
part 6: Module 6
session 28: Matlab Code for Gauss Seidel Method
session 29: Power Method for Solving Eigenvalues of a Matrix
session 30: Power Method for Solving Eigenvalues of a Matrix (Contd.)
session 31: Gershgorin Circle Theorem for Estimating Eigenvalues of a Matrix
session 32: Gershgorin Circle Theorem for Estimating Eigenvalues of a Matrix
session 33: Matlab Code for Power Method/ Shifted Inverse Power Method
part 7: Module 7
session 34: Interpolation
session 35: Interpolation (Contd.)
session 36: Interpolation (Contd.)
session 37: Interpolating Polynomial Using Newton's Forward Difference Formula
session 38: Error Estimates in Polynomial Approximation
session 39: Interpolating Polynomial Using Newton's Backward Difference Formula
part 8: Module 8
session 40: Stirling's Formula and Lagrange's Interpolating Polynomial
session 41: In Continuation of Lagrange's Interpolating Formula
session 42: Interpolating Polynomial Using Newton's Divided Difference Formula
session 43: Examples Based on Lagrange's and Newton's Divided Difference Interpolation
session 44: Spline Interpolation
session 45: Cubic Spline
part 9: Module 9
session 46: Cubic Spline (contd.)
session 47: Curve Fitting
session 48: Quadratic Polynomial Fitting and Code for Lagrange's Interpolating Polynomial using Octave
session 49: Matlab Code for Newton's Divided Difference and Least Square Approximation
session 50: Matlab Code for Cubic Spline
session 51: Numerical Differentiation
part 10: Module 10
session 52: Various Numerical Differentiation Formulas
session 53: Higher Order Accurate Numerical Differentiation Formula For First Order Derivative
session 54: Higher Order Accurate Numerical Differentiation Formula For Second Order Derivative
session 55: Numerical Integration
session 56: Trapezoidal Rule for Numerical Integration
session 57: Simpson's 1/3 rule for Numerical Integration
part 11: Module 11
session 58: Simpson's 3/8 Rule for Numerical Integration
session 59: Method of Undetermined Coefficients
session 60: Octave Code for Trapezoidal and Simpson's Rule
session 61: Taylor Series Method for Ordinary Differential Equations
session 62: Linear Multistep Method (LMM) for Ordinary Differential Equations
part 12: Module 12
session 63: Convergence and Zero Stability for LMM
session 64: Matlab/Octave Code for Initial Value Problems
session 65: Advantage of Implicit and Explicit Methods Over Each other via Matlab/Octave Codes for Initial value Problem

Catalogue records

nptel: 111102137 (manifestation)
nptel_video: 111102137 (manifestation)