Lecture 19 - Eigen Values of A Matrix

Course Lectures

• Lecture 1 - Programing Basics

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• Lecture 2 - Introduction to Pointers

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• Lecture 3 - Pointers And Arrays

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• Lecture 4 - External Functions and Argument Passing

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• Lecture 5 - Representation of Numbers

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• Lecture 6 - Numerical Error

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• Lecture 7 - Error Propagation and Stability

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• Lecture 8 - Polynomial Interpolation-1

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• Lecture 9 - Polynomial Interpolation-2

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• Lecture 10 - Error In Interpolation Polynomial

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• Lecture 11 - Polynomial Interpolation

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• Lecture 12 - Cubic Spline Interpolation

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• Lecture 13 - Data Fitting : Linear Fit

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• Lecture 14 - Data Fitting : Linear Fit

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• Lecture 15 - Data Fitting : Non Linear Fit

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• Lecture 16 - Matrix Elimation and Solution

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• Lecture 17 - Solution To Linear Equations

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• Lecture 18 - Matrix Elimination

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• Lecture 19 - Eigen Values of A Matrix

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• Lecture 20 - Eigen Values And Eigen Vectors

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• Lecture 21 - Solving NonLinear Equations

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• Lecture 22 - Solving NonLinear Equations Newton

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• Lecture 23 - Methods For Solving NonLinear Equations

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• Lecture 24 - System of NonLinear Equations

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• Lecture 25 - Numerical Derivations

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• Lecture 26 - High order Derivatives From Difference Formula

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• Lecture 27 - Numerical Integration - Basic Rules

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• Lecture 28 - Comparison of Different Basic Rules

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• Lecture 29 - Gaussian Rules

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• Lecture 30 - Comparison of Gaussian Rules

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• Lecture 31 - Solving Ordinary Differential Equations

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• Lecture 32-Solving ordinary differential equations

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• Lecture 33 - Adaptive step size Runge Kutta scheme

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• Lecture 34 - Partial Differential Equations

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• Lecture 35 - Explicit and Implicit Methods

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• Lecture - 36 The Crank - Nicholson Scheme For Two Spatial

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• Lecture 37 - Fourier Transforms

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• Lecture 38 Fast Fourier Transforms

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