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Pbk. Contents Foreword Preface Acknowledgments 1 Errors and Approximations 2 Fundamental Concepts from the Theory of Equations 3 Simultaneous Linear Equations 4 Eigen values and eigenvectors 5 Finite Differences 6 Interpolation 7 Numerical Differentiation 8 Numerical Integration 9 Numerical Solution of Ordinary Differential Equations 10 Numerical solution of Partial Differential Equations IndexA number of unique features make this book different from other existing books in the field Designed for the core course on the subject this book seeks to provide students with fundamentals of numerical methods Logical arrangement of topics clarity of presentation and illustration through maximum examples and exercise aid the student in becoming adept at applying the methods This book is written keeping in mind undergraduate and postgraduate students of Engineering and Science students of all disciplines 406 pp.

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Etat : Hervorragend. Zustand: Hervorragend | Seiten: 218 | Sprache: Englisch | Produktart: Bücher.

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paperback. Etat : New. Language:Chinese.Paperback. Pub Date: 2024-01 Pages: 1.392 Publisher: Tsinghua University Press Numerical Methods in Python - Solving Engineering and Scientific Problems is written for students who want to learn and apply numerical methods to solve engineering and scientific problems. The book provides sufficient theoretical knowledge. If you have read the sister book of this book MATLAB Implementation of Numerical Methods in Engineering and Science (4th Edition). you will find that the trans.

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paperback. Etat : New. Ship out in 2 business day, And Fast shipping, Free Tracking number will be provided after the shipment.Pages Number: 592 Publisher: Tsinghua University Press Pub. Date :2009-5-1. Contents: Section part modeling. computer and Error Analysis Chapter 1. mathematical modeling. numerical methods and problem-solving a simple mathematical model of 31.1 41.2 Engineering and science involved in book conservation laws 101.3 131.4 Numerical Methods for Problem 14 in Chapter 2 Environmental 202.2 192.1 MATLAB MATLAB based assignments 212.2.1 212.2.2 array scalar. vector and matrix operators 252.2.4 232.2.3 colon linspace and logspace functions 262.3 262.4 using the built-in math functions plot 332.6 302.5 362.7 Other resources case studies: exploratory data analysis 372.8 Exercises 39 Chapter 3 453.1 M file written MATLAB program script file 463.1.2 463.1.1 473.1.3 function file Functions 493.2 503.3 structured programming input and output decisions 553.3.2 543.3.1 623.4 Nested loops will function with the indentation 663.5 passing an anonymous function M-file 693.5.1 713.5.3 693.5.2 function function to pass parameters 733.6 Case Study: bungee jumping speed of 743.7 player Exercises 78 Chapter 4. rounding and truncation error 854.1 error 864.1.1 864.1.2 accuracy and precision rounding error is defined in 874.2 the number of computer error 904.2.1 904.2.2 that the number of computer arithmetic Taylor series truncation error 974.3.1 954.3 984.3.2 Taylor series expansion with more than 1014.3.3 1034.3.4 Taylor series truncation error is estimated the total error of numerical difference 1044.4 1084.4.1 1094.4.2 numerical error analysis of differential values error control 1114.5 gross error. model error and data uncertainty gross error 1124.5.2 1124.5.1 1134.5.3 data model error uncertainty 1134.6 Exercise Part 113 Section Roots and Optimization Chapter 5 Roots: demarcation Method 1215.1 in the field of engineering and scientific graphics method 1235.3 1225.2 rooting problem with the initial guess value of the demarcation law dichotomy 1295.5 1255.4 1345.6 trial counterpoint case study: greenhouse gases and water 1375.7 Exercises 141 Chapter 6 equation Roots: open method 1476.1 1486.2 a simple fixed point iteration Newton - La Fusen secant method 1526.3 1576.4 MATLAB function: fzero 1596.5 1626.6 polynomial case study: pipe friction 1656.7 Exercises 169 Chapter 7 Introduction and background optimization 1757.1 1767.2 most one-dimensional golden section search optimization 1787.2.1 1797.2.2 1847.2.3 MATLAB parabolic interpolation function: fminbnd 1867.3 1877.4 multidimensional optimization case study: balance exercises with minimal potential energy 1897.5 Part 190 Section Chapter 8 linear equations and linear algebra overview of matrix algebra matrix 2038.1 2058.1.1 Matrix symbol matrix operation rules 2078.1.3 2058.1.2 linear algebraic equations expressed in matrix form 2128.2 using MATLAB to solve linear algebraic equations 2138.3 Case Study: circuit current and voltage 2158.4 Exercises 218 Chapter 9 2239.1 Gauss elimination method to solve equations 2249.1.1 small cartography 2249.1.2 2259.1.3 unknown determinants and Cramer rule elimination method 2289.2 simple Gaussian elimination 2299.2.1 MATLABM file: GaussNaive 2329.2.2 number of operations 2339.3 pivoting 2359.4 2389.5 tridiagonal equations Case Study: Exercise hot rod model 2409.6 LU decomposition 242 Chapter 10 Overview 25010.2 24910.1 LU decomposition and Gaussian elimination LU decomposition decomposition 25610.4 25110.3 Chu Lie Siji MATLAB left division operation 25910.5 Exercises 259 Chapter 11 matrix inverse and the inverse of the matrix condition number 26311.1 26311.1.1 26311.1.2 inverse matrix calculation of excitation - Response error analysis and calculation 26511.2 equations of vector and matrix condition number 26711.2.1 norm matrix condition number 26911.2.3 26811.2.2 calculated using MATLAB norm and condition number 27111.3 Case study: indoor air pollution 27211.4 E.

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