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Introductory methods of numerical analysis

Introductory Methods of. Numerical Analysis. Fifth Edition. S.S. SASTRY. Formerly Scientist/Engineer SF. Vikram Sarabhai Space Centre. Trivandrum.



Introductory methods of numerical analysis

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Introductory Methods of Numerical Analysis

Introductory Methods of. Numerical Analysis. Fifth Edition. S.S. SASTRY. Formerly Scientist/Engineer SF. Vikram Sarabhai Space Centre. Trivandrum.



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Introductory Methods of. Numerical Analysis. Fifth Edition. S.S. SASTRY. Formerly Scientist/Engineer SF. Vikram Sarabhai Space Centre. Trivandrum.



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Introductory Methods of Numerical Analysis - S.S. Sastry

Introductory Methods of. Numerical Analysis. Fifth Edition. S.S. SASTRY. Formerly Scientist/Engineer SF. Vikram Sarabhai Space Centre. Trivandrum.



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2 3 I Acceleration of Convergence: Aitken's d2-process The Method of False Position Newton-Raphson Method 2 5 I Generalized Newton's Method Ramanujan's Method Muller's Method Graeffe's Root-Squaring Method Lin-Bairstow's Method The Quotient-Difference Method Solution of Systems of Nonlinear Equations 2 11 1 The Method of Iteration



FIFTH EDITION Introductory Methods of Numerical Analysis

INTRODUCTORY METHODS OF NUMERICAL ANALYSIS Fifth Edition S S Sastry 2012 by PHI Learning Private Limited New Delhi All rights reserved No partof this book may be reproduced in any form by mimeograph or any othermeans without permission in writing from the publisher ISBN-978-81-203-4592-8



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What is numerical analysis?

    Introduction Numerical analysis is a branch of Mathematics that deals with devising e?cient methods for obtaining numerical solutions to di?cult Mathematical problems. Most of the Mathematical problems that arise in science and engineering are very hard and sometime impossible to solve exactly.

What are the three parts of numerical analysis?

    Numerical analysis include three parts. The ?rst part of the subject is about the development of a method to a problem. The second part deals with the analysis of the method, which includes the error analysis and the e?ciency analysis.

Why do scientists use numerical approximation?

    Due to the immense development in the computational technology, numerical approximation has become more popular and a modern tool for scientists and engineers. As a result many scienti?c softwares are developed (for instance, Matlab, Mathematica, Maple etc.) to handle more di?cult problems in an e?cient and easy way.

FIFTH EDITION

Introductory

Methods of

Numerical

Analysis

S.S. Sastry

Introductory Methods of Numerical Analysis

Introductory Methods of

Numerical Analysis

Fifth Edition

S.S. SASTRY

Formerly, Scientist/Engineer SF

Vikram Sarabhai Space Centre

Trivandrum

New Delhi-110001

2012
INTRODUCTORY METHODS OF NUMERICAL ANALYSIS, Fifth Edition

S.S. Sastry

© 2012 by PHI Learning Private Limited, New Delhi. All rights reserve d. No part of this book may be reproduced in any form, by mimeograph or any other means, without permission in writing from the publisher.

ISBN-978-81-203-4592-8

The export rights of this book are vested solely with the publisher.

Forty-fifth Printing (Fifth Edition)

June, 2012

Published by Asoke K. Ghosh, PHI Learning Private Limited, M-97, Connaug ht Circus, New Delhi-110001 and Printed by Rajkamal Electric Press, Plot No . 2,

Phase IV, HSIDC, Kundli-131028, Sonepat, Haryana.

To

My Grandsons

Venkata Bala Nagendra

Venkata Badrinath

Preface xiii

1. Errors in Numerical Calculations 1-21

1.1 Introduction 1

1.1.1Computer and Numerical Software 3

1.1.2Computer Languages 3

1.1.3Software Packages 4

1.2 Mathematical Preliminaries 5

1.3 Errors and Their Computations 7

1.4 A General Error Formula 12

1.5 Error in a Series Approximation 14

Exercises 19

Answers to Exercises 21

2. Solution of Algebraic and Transcendental Equations 22-72

2.1 Introduction 22

2.2 Bisection Method 23

2.3 Method of False Position 28

2.4 Iteration Method 31

2.5 Newton-Raphson Method 37

2.6 Ramanujan's Method 43

2.7 Secant Method 49

2.8 Muller's Method 51

2.9 Graeffe's Root-Squaring Method 53

2.10 Lin-Bairstow's Method 56

2.11Quotient-Difference Method 58

Contents

vii

Contentsviii

2.12 Solution to Systems of Nonlinear Equations 62

2.12.1Method of Iteration 62

2.12.2 Newton-Raphson Method 64

Exercises 68

Answers to Exercises 71

3. Interpolation 73-125

3.1 Introduction 73

3.2 Errors in Polynomial Interpolation 74

3.3 Finite Differences 75

3.3.1Forward Differences 75

3.3.2Backward Differences 77

3.3.3Central Differences 78

3.3.4Symbolic Relations and Separation of Symbols 79

3.4 Detection of Errors by Use of Difference Tables 82

3.5 Differences of a Polynomial 83

3.6 Newton's Formulae for Interpolation 84

3.7 Central Difference Interpolation Formulae 90

3.7.1Gauss' Central Difference Formulae 90

3.7.2Stirling's Formula 94

3.7.3Bessel's Formula 94

3.7.4Everett's Formula 96

3.7.5Relation between Bessel's and Everett's Formulae 96

3.8 Practical Interpolation 97

3.9 Interpolation with Unevenly Spaced Points 101

3.9.1Lagrange's Interpolation Formula 101

3.9.2Error in Lagrange's Interpolation Formula 107

3.9.3Hermite's Interpolation Formula 108

3.10 Divided Differences and Their Properties 111

3.10.1Newton's General Interpolation Formula 113

3.10.2Interpolation by Iteration 115

3.11Inverse Interpolation 116

3.12 Double Interpolation 118

Exercises 119

Answers to Exercises 125

4. Least Squares and Fourier Transforms 126-180

4.1 Introduction 126

4.2 Least Squares Curve Fitting Procedures 126

4.2.1Fitting a Straight Line 127

4.2.2Multiple Linear Least Squares 129

4.2.3Linearization of Nonlinear Laws 130

4.2.4Curve Fitting by Polynomials 133

4.2.5Curve Fitting by a Sum of Exponentials135

Contentsix

4.3 Weighted Least Squares Approximation 138

4.3.1Linear Weighted Least Squares Approximation 138

4.3.2Nonlinear Weighted Least Squares Approximation 140

4.4 Method of Least Squares for Continuous Functions 140

4.4.1Orthogonal Polynomials 143

4.4.2Gram-Schmidt Orthogonalization Process 145

4.5 Approximation of Functions 148

4.5.1Chebyshev Polynomials 149

4.5.2Economization of Power Series 152

4.6 Fourier Approximation 153

4.6.1Fourier Transform 156

4.6.2Discrete Fourier Transform (DFT) 157

4.6.3Fast Fourier Transform (FFT) 161

4.6.4Cooley-Tukey Algorithm 161

4.6.5Sande-Tukey Algorithm (DIF-FFT) 170

4.6.6Computation of the Inverse DFT 174

Exercises 176

Answers to Exercises 179

5. Spline Functions 181-206

5.1 Introduction 181

5.1.1Linear Splines 182

5.1.2Quadratic Splines 183

5.2 Cubic Splines 185

5.2.1Minimizing Property of Cubic Splines 191

5.2.2Error in the Cubic Spline and Its Derivatives 192

5.3 Surface Fitting by Cubic Splines 193

5.4 Cubic B-splines 197

5.4.1Representation of B-splines 198

5.4.2Least Squares Solution 203

5.4.3Applications of B-splines 203

Exercises 204

Answers to Exercises 206

6. Numerical Differentiation and Integration 207-254

6.1 Introduction 207

6.2 Numerical Diferentiation 207

6.2.1Errors in Numerical Differentiation 212

6.2.2Cubic Splines Method 214

6.2.3Differentiation Formulae with Function Values 216

6.3 Maximum and Minimum Values of a Tabulated Function 217

6.4 Numerical Integration218

6.4.1Trapezoidal Rule 219

6.4.2Simpson's 1/3-Rule

221

6.4.3Simpson's 3/8-Rule 222

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