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Home | About | Resources | Reqmts | Search | Faqs | Site Index | Contact | KEYWORD | 1st Time Visitor |
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Intro | Differentiation | Nonlinear Eqns | Simul Linear Eqns | Interpolation | Regression | Integration | ODE |
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RESOURCES By Topic, Major & Language | EBooks | Textbook | Physical Examples | PowerPoint | Simulations | Anecdotes | Assessment | Publications Welcome to the website for a Numerical Methods course for engineering undergraduates. It is dedicated to reaching a large audience of undergraduate students through its holistic but customized approach. Holistically, the resources review background information; present numerical methods through notes, presentations, simulations and assessments; show how what they learned is applied in real life; tell stories to illustrate special topics and pitfalls; and give historical perspectives. From a customized perspective, the user can choose a major of choice - Chemical, Civil, Computer, Electrical, General, Industrial or Mechanical Engineering. You can choose Maple, Mathcad, Mathematica or Matlab as one of the packages used to illustrate algorithms, convergence and pitfalls of the numerical methods.
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EBOOKS
Based on feedback from the external evaluators and the users of the web-based resources, the eBooks are no longer available. But, we have something better and compact!
The major purpose of the eBooks was putting all the resources in one document. The feedback overwhelmingly mentioned that this objective is better served by the one-page resources that are available for each topic |
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TEXTBOOK: NUMERICAL METHODS WITH APPLICATIONS Abridged Print Version Available
Authors: Autar K Kaw | Co-Author: Egwu E Kalu | Future Co-Author: Duc Nguyen Contributors: Glen Besterfield, Sudeep Sarkar, Henry Welch, Ali Yalcin | Future Contributor: Venkat Bhethanabotla
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1: Introduction, Approximation and Errors |
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Chapter 01.01 Introduction to Scientific Computing [PDF] [DOC] [MORE] Chapter 01.02 Measuring Errors [PDF] [DOC] [MORE] Chapter 01.03 Sources of Error [PDF] [DOC] [MORE] Chapter 01.04 Binary Representation of Numbers [PDF] [DOC] [MORE] Chapter 01.05 Floating Point Representation [PDF] [DOC] [MORE] Chapter 01.06 Propagation of Errors [PDF] [DOC] [MORE] Chapter 01.07 Taylor Series Revisited [PDF] [DOC] [MORE]
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2: Differentiation |
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Chapter 02.01 Primer on Differential Calculus [PDF] [DOC] Chapter 02.02 Differentiation of Continuous Functions [PDF] [DOC] [MORE] Chapter 02.03 Differentiation of Discrete Functions [PDF] [DOC] [MORE]
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3: Nonlinear Equations |
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Chapter 03.01 Solving Quadratic Equations Exactly [PDF] [DOC] [MORE] Chapter 03.02 Solving Cubic equations Exactly [PDF] [DOC] Chapter 03.03 Bisection Method [PDF] [DOC] [MORE] Chapter 03.04 Newton-Raphson Method [PDF] [DOC] [MORE] Chapter 03.05 Secant Method [PDF] [DOC] [MORE]
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4: Simultaneous Linear Equations |
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Chapter 04.01 Introduction [PDF] [DOC] Chapter 04.02 Vectors [PDF] [DOC] Chapter 04.03 Binary Matrix Operations [PDF] [DOC] Chapter 04.04 Unary Matrix Operations [PDF] [DOC] Chapter 04.05 System of Equations [PDF] [DOC] Chapter 04.06 Gaussian Elimination Method [PDF] [DOC] [MORE] Chapter 04.07 LU Decomposition Method [PDF] [DOC] [MORE]
Chapter 04.08 How does Gauss-Seidel method work?
[PDF] [DOC]
[MORE] Chapter 04.10 Eigenvalues and Eigenvectors [PDF] [DOC]
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5: Interpolation |
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Chapter 05.01 History of Interpolation [PDF] [DOC] Chapter 05.02 Direct Method [PDF] [DOC] [MORE] Chapter 05.03 Newton's Divided Difference Method [PDF] [DOC] [MORE] Chapter 05.04 Lagrange Method [PDF] [DOC] [MORE] Chapter 05.05 Spline Method [PDF] [DOC] [MORE] Chapter 05.06 The lurking dangers of extrapolation! [PDF] [DOC] Chapter 05.07 Why is higher order interpolation a bad idea? [PDF] [DOC] Chapter 05.08 Why do we need spline interpolation [PDF] [DOC] Chapter 05.09 How choice of points of interpolation affects approximations! [PDF] [DOC] Chapter 05.10 How splines can help in developing a shorter path for a robot! [PDF] [DOC]
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6: Regression |
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Chapter 06.01 Primer on statistical terminology [PDF] [DOC] Chapter 06.02 Introduction to Regression [PDF] [DOC] Chapter 06.03 Linear Regression [PDF] [DOC] [MORE] Chapter 06.04 Nonlinear Regression [PDF] [DOC] [MORE]
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7: Integration |
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Chapter 07.01 Primer on Integral Calculus [PDF] [DOC]
Chapter 07.02 Trapezoidal Rule
[PDF]
[DOC]
[MORE]
Chapter 07.04 Romberg Rule
[PDF]
[DOC]
[MORE]
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8: Ordinary Differential Equations |
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Chapter 08.01 Primer on Ordinary Differential Equations [PDF] [DOC] Chapter 08.02 Euler's method [PDF] [DOC] [MORE] Chapter 08.03 Runge-Kutta 2nd order method [PDF] [DOC] [MORE] Chapter 08.04 Runge-Kutta 4th order method [PDF] [DOC] [MORE] Chapter 08.05 On solving higher order & coupled ordinary differential equations [PDF] [DOC] Chapter 08.06 Shooting Method [PDF] [DOC] [MORE] Chapter 08.07 Finite Difference Method [PDF] [DOC] [MORE]
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9: Fast Fourier Transforms |
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2009 |
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10: PARTIAL DIFFERENTIAL EQUATIONS |
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2010 |
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11: optimization |
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2010 |
Companion Tools for the Textbook
Video Lectures | eBooks | PowerPoint Presentations | Worksheets | Multiple-Choice Tests | Anecdotes
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POWER POINT PRESENTATIONS |
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INTRODUCTION TO SCIENTIFIC COMPUTING Introduction to numerical methods [PDF] [PPT] Binary representation of numbers [PDF] [PPT] Floating point representation of numbers [PDF] [PPT] Propagation of errors [PDF] [PPT]
differentiation Continuous functions [PDF] [PPT] Discrete functions [PDF] [PPT] Effect of step size on accuracy of numerical first derivative: Forward Divided Difference [PDF] [PPT] Effect of step size on accuracy of numerical first derivative: Backward Divided Difference [PDF] [PPT] Effect of step size on accuracy of numerical first derivative: Central Divided Difference [PDF] [PPT]
Nonlinear Equations Newton-Raphson Method [PDF] [PPT]
SIMULTANEOUS LINEAR Equations Gaussian Elimination [PDF] [PPT] LU Decomposition method [PDF] [PPT] Gauss-Seidal method [PDF] [PPT]
Interpolation Newton's Divided Difference Method [PDF] [PPT]
REGRESSION Nonlinear regression [PDF] [PPT]
Integration
Trapezoidal Rule
[PDF]
[PPT]
Romberg Rule
[PDF]
[PPT]
ordinary differential equations Runge-Kutta 2nd order Method [PDF] [PPT]
Runge-Kutta 4th order Method
[PDF]
[PPT] |
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WORKSHEETS |
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INTRODUCTION TO SCIENTIFIC COMPUTING |
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Measuring Errors |
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True Error [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Approximate Error [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB |
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Binary Representation |
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Decimal to binary representation [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Binary to decimal representation [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Measuring Errors |
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Decimal to floating point representation [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Binary to floating point representation [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Propagation of Errors |
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Differentiation |
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Continuous Functions |
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Forward Divided Difference [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Backward Divided Difference [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Central Divided Difference [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Continuous functions Second Order Derivative [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Discrete Data |
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Discrete functions [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Nonlinear Equations |
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Bisection Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Pitfall: Slow convergence of bisection method simulation [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Newton-Raphson Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Pitfall: Division by zero [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Pitfall: Slow Convergence at Inflection Points [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Pitfall: Root jumps over several roots [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Pitfall: Roots oscillates around local maxima and minima [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Secant Method |
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Simulation of secant method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence Simulation of secant method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Pitfall: Division by zero in secant method simulation [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Pitfall: Root jumps over several roots in secant method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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SIMULTANEOUS LINEAR EQUATIONS |
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Gaussian Elimination |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Gauss-Seidel Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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LU Decomposition |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Interpolation |
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Direct Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Newton's Divided Difference Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Lagrange Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Spline Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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REGRESSION |
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Linear Regression |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Nonlinear Regression |
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Without Data Linearization [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] With Data Linearization [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Polynomial Regression [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Comparing with and without Data Linearization [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Adequacy of a Regression Model |
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Adequacy [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Integration |
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Trapezoidal Rule |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Simpson's 1/3rd Rule |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Romberg Rule |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Gauss-Quadrature Rule |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Integrating Discrete Functions |
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Integrating discrete functions [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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ORDINARY DIFFERENTIAL EQUATIONS |
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Euler's Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Runge-Kutta 2nd order Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Runge-Kutta 4th order Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] Convergence [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Shooting Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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Finite Difference Method |
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Method [MAPLE] [MATHCAD] [MATHEMATICA] [MATLAB] |
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ANECDOTES |
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DIFFERENTIATION |
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Effect of step size on accuracy of numerical first derivative: Forward Divided Difference [PDF] [PPT] Effect of step size on accuracy of numerical first derivative: Backward Divided Difference[PDF][PPT] Effect of step size on accuracy of numerical first derivative: Central Divided Difference [PDF] [PPT] Comparing the Forward Divided Difference, Backward Divided Difference Central Divided Difference [PDF] [MWS] | [PDF] [MCD] | [PDF] [NB]|[PDF] [MFILE] Effect of Significant Digits on the Value of the Numerical Derivative [PDF] [MWS] | [PDF] [MCD]|[PDF] [NB]|[PDF] [MFILE] |
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NONLINEAR EQUATIONS |
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Quest for cubic equation solution [PDF] [DOC]
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INTERPOLATION |
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History of Interpolation [PDF] [DOC] Dangers of extrapolation through NASDAQ, [PDF] [DOC]|[MWS] [MCD] [MFILE] [NBM] Higher order interpolation is a bad idea [PDF] [DOC]| [MWS] [MCD] [MFILE] [NBM] Comparison of spline & polynomial interpolation [PDF] [DOC]|[MWS] [MCD] [MFILE] [NBM] Choice of points of interpolation affects approximations [PDF] [DOC]|[MWS] [MCD] [MFILE] [NBM] Splines help in developing a shorter path for a robot [PDF] [DOC]|[MWS] [MCD] [MFILE] [NBM]
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INTEGRATION |
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What is integration? [PDF] [DOC] A Primer on Integral Calculus [PDF] [DOC]
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ORDINARY DIFFERENTIAL EQUATIONS |
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MULTIPLE CHOICE QUESTIONS
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Introduction to Numerical Methods [HTML] [FLASH] [PDF] [DOC] |
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Floating Point Representation of Numbers [HTML] [FLASH] [PDF] [DOC] |
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Secant Method [HTML] [FLASH] [PDF] [DOC]
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Newton's Divided Difference Method [HTML] [FLASH] [PDF] [DOC] |
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Spline Method [HTML] [FLASH] [PDF] [DOC]
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Nonlinear Regression [HTML] [FLASH] [PDF] [DOC]
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Gauss-Quadrature method [HTML] [FLASH] [PDF] [DOC]
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