PirateBay Download | engeln m uuml llges g uhlig f numerical algorithms c 1996

engeln m uuml llges g uhlig f numerical algorithms c 1996

Type:: E-books
Files:: 1
Size:: 34.5 MB
Uploaded On:: Oct. 30, 2024, 2:30 p.m.
Added By:: andryold1
Seeders:: 6
Leechers:: 8
Info Hash:: D9932B74B1F375D08C05551380B4622852D59E51

Textbook in PDF format Computer Numbers, Error Analysis, Conditioning, Stability of Algorithms and Operations Count Definition of Errors Decimal Representation of Numbers Sources of Errors Input Errors Procedural Errors Error Propagation and the Condition of a Problem The Computational Error and Numerical Stability of an Algorithm Operations Count, et cetera Nonlinear Equations in One Variable Introduction Definitions and Theorems on Roots General Iteration Procedures How to Construct an Iterative Process Existence and Uniqueness of Solutions Convergence and Error Estimates of Iterative Procedures Practical Implementation Order of Convergence of an Iterative Procedure Definitions and Theorems Determining the Order of Convergence Experimentally Newton's Method Finding Simple Roots A Damped Version of Newton's Method Newton's Method for Multiple Zeros; a Modified Newton's Method Regula Falsi Regula Falsi for Simple Roots Modified Regula Falsi for Multiple Zeros Simplest Version of the Regula Falsi Steffensen Method Steffensen Method for Simple Zeros Modified Steffensen Method for Multiple Zeros Inclusion Methods Bisection Method Pegasus Method Anderson-Bjorck Method The King and the Anderson-Bjorck-King Methods, the Illinois Method Zeroin Method Efficiency of the Methods and Aids for Decision Making Roots of Polynomials Preliminary Remarks The Horner Scheme First Level Horner Scheme for Real Arguments First Level Horner Scheme for Complex Arguments Complete Horner Scheme for Real Arguments Applications Methods for Finding all Solutions of Algebraic Equations Preliminaries Muller's Method Bauhuber's Method The Jenkins-'!raub Method The Laguerre Method Hints for Choosing a Method Direct Methods for Solving Systems of Linear Equations The Problem Definitions and Theoretical Background Solvability Conditions for Systems of Linear Equations The Factorization Principle GauE Algorithm GauE Algorithm with Column Pivot Search Pivot Strategies Computer Implementation of GauB Algorithm GauB Algorithm for Systems with Several Right Hand Sides Matrix Inversion via GauB Algorithm Linear Equations with Symmetric Strongly Nonsingular System Matrices The Cholesky Decomposition The Conjugate Gradient Method The GauB - Jordan Method The Matrix Inverse via Exchange Steps Linear Systems with Tridiagonal Matrices Systems with Tridiagonal Matrices Systems with Tridiagonal Symmetric Strongly Nonsingular Matrices Linear Systems with Cyclically Tridiagonal Matrices Systems with a Cyclically Tridiagonal Matrix Systems with Symmetric Cyclically Tridiagonal Strongly Nonsingular Matrices Linear Systems with Five-Diagonal Matrices Systems with Five-Diagonal Matrices Systems with Five-Diagonal Symmetric Matrices Linear Systems with Band Matrices Solving Linear Systems via Householder Transformations Errors, Conditioning and Iterative Refinement Errors and the Condition Number Condition Estimates Improving the Condition Number Iterative Refinement Systems of Equations with Block Matrices Preliminary Remarks GauB Algorithm for Block Matrices GauB Algorithm for Block Tridiagonal Systems ther Block Methods The Algorithm of Cuthill-McKee for Sparse Symmetric Matrices Recommendations for Selecting a Method Iterative Methods for Linear Systems Preliminary Remarks Vector and Matrix Norms The Jacobi Method The GauB-Seidel Iteration A Relaxation Method using the Jacobi Method A Relaxation Method using the GauB-Seidel Method Iteration Rule Estimate for the Optimal Relaxation Coefficient, an Adaptive SOR Method Systems of Nonlinear Equations General Iterative Methods Special Iterative Methods Newton Methods for Nonlinear Systems The Basic Newton Method Damped Newton Method for Systems Regula Falsi for Nonlinear Systems Method of Steepest Descent for Nonlinear Systems Brown's Method for Nonlinear Systems Choosing a Method Eigenvalues and Eigenvectors of Matrices Basic Concepts Diagonalizable Matrices and the Conditioning of the Eigenvalue Problem Vector Iteration The Dominant Eigenvalue and the Associated Eigenvector of a Matrix Determination of the Eigenvalue Closest to Zero Eigenvalues in Between The Rayleigh Quotient for Hermitian Matrices The Krylov Method Determining the Eigenvalues Determining the Eigenvectors Eigenvalues of Positive Definite Tridiagonal Matrices, the QD Algorithm Transformation to Hessenberg Form, the LR and QR Algorithms Transformation of a Matrix to Upper Hessenberg Form The LR Algorithm The Basic QR Algorithm Eigenvalues and Eigenvectors of a Matrix via the QR Algorithm Decision Strategy Linear and Nonlinear Approximation Linear Approximation Statement of the Problem and Best Approximation Linear Continuous Root-Mean-Square Approximation Discrete Linear Root-Mean-Square Approximation Normal Equations for Discrete Linear Least Squares Discrete Least Squares via Algebraic Polynomials and Orthogonal Polynomials Linear Regression, the Least Squares Solution Using Linear Algebraic Polynomials Solving Linear Least Squares Problems using Householder Transformations Approximation of Polynomials by Chebyshev Polynomials Best Uniform Approximation Approximation by Chebyshev Polynomials Approximation of Periodic Functions and the FFT Root-Mean-Square Approximation of Periodic Functions Trigonometric Interpolation Complex Discrete Fourier Transformation (FFT) Error Estimates for Linear Approximation Estimates for the Error in Best Approximation Error Estimates for Simultaneous Approximation of a Function and its Derivatives Approximation Error Estimates using Linear Projection Operators Nonlinear Approximation Transformation Method for Nonlinear Least Squares Nonlinear Root-Mean-Square Fitting Decision Strategy Polynomial and Rational Interpolation The Problem Lagrange Interpolation Formula Lagrange Formula for Arbitrary Nodes Lagrange Formula for Equidistant Nodes The Aitken Interpolation Scheme for Arbitrary Nodes Inverse Interpolation According to Aitken Newton Interpolation Formula Newton Formula for Arbitrary Nodes Newton Formula for Equidistant Nodes Remainder of an Interpolation and Estimates of the Interpolation Error Rational Interpolation Interpolation for Functions in Several Variables Lagrange Interpolation Formula for Two Variables Shepard Interpolation Hints for Selecting an Appropriate Interpolation Method Interpolating Polynomial Splines for Constructing Smooth Curves Cubic Polynomial Splines Definition of Interpolating Cubic Spline Functions Computation of Non-Parametric Cubic Splines Computing Parametric Cubic Splines Joined Interpolating Polynomial Splines Convergence and Error Estimates for Interpolating Cubic Splines Hermite Splines of Fifth Degree Definition of Hermite Splines Computation of Non-Parametric Hermite Splines Computation of Parametric Hermite Splines Hints for Selecting Appropriate Interpolating or Approximating Splines Cubic Fitting Splines for Constructing Smooth Curves The Problem Definition of Fitting Spline Functions Non-Parametric Cubic Fitting Splines Contents XIX Parametric Cubic Fitting Splines Decision Strategy Two-Dimensional Splines, Surface Splines, Bezier Splines, B-Splines Interpolating Two-Dimensional Cubic Splines for Constructing Smooth Surfaces Two-Dimensional Interpolating Surface Splines Bezier Splines Bezier Spline Curves Bezier Spline Surfaces Modified Interpolating Cubic Bezier Splines B-Splines B-Spline-Curves B-Spline-Surfaces Hints Akima and Renner Subsplines Akima Subsplines Renner Sub splines Rounding of Corners with Akima and Renner Splines Approximate Computation of Arc Length Selection Hints Numerical Differentiation The Task Differentiation Using Interpolating Polynomials Differentiation via Interpolating Cubic Splines Differentiation by the Romberg Method Decision Hints Numerical Integration Preliminary Remarks Interpolating Quadrature Formulas Newton-Cotes Formulas The Trapezoidal Rule Simpson's Rule The / Formula Other Newton-Cotes Formulas The Error Order of Newton-Cotes Formulas Maclaurin Quadrature Formulas The Tangent Trapezoidal Formula Other Maclaurin Formulas Euler-Maclaurin Formulas Chebyshev Quadrature Formulas GauB Quadrature Formulas Calculation of Weights and Nodes of Generalized Gaussian Quadrature Formulas Clenshaw-Curtis Quadrature Formulas Romberg Integration Error Estimates and Computational Errors Adaptive Quadrature Methods Convergence of Quadrature Formulas Hints for Choosing an Appropriate Method Numerical Cubature The Problem Interpolating Cubature Formulas Newton-Cotes Cubature Formulas for Rectangular Regions Newton-Cotes Cubature Formulas for Triangles Romberg Cubature for Rectangular Regions GauB Cubature Formulas for Rectangles GauB Cubature Formulas for Triangles Right Triangles with Legs Parallel to the Axis General Triangles Riemann Double Integrals using Bicubic Splines Decision Strategy Initial Value Problems for Ordinary Differential Equations The Problem Principles of the Numerical Methods One-Step Methods The Euler-Cauchy Polygonal Method The Improved Euler-Cauchy Method The Predictor-Corrector Method of Heun Explicit Runge-Kutta Methods Construction of Runge-Kutta Methods The Classical Runge-Kutta Method A List of Explicit Runge-Kutta Formulas Embedding Formulas Implicit Runge-Kutta Methods of Gaussian Type Consistence and Convergence of One-Step Methods Error Estimation and Step Size Control Error Estimation Automatic Step Size Control, Adaptive Methods for Initial Value Problems Multi-Step Methods The Principle of Multi-Step Methods The Adams-Bashforth Method The Predictor-Corrector Method of Adams-Moulton The Adams-Stormer Method Error Estimates for Multi-Step Methods Computational Error of One-Step and Multi-Step Methods Bulirsch-Stoer-Gragg Extrapolation Stability Preliminary Remarks Stability of Differential Equations Stability of the Numerical Method Stiff Systems of Differential Equations The Problem Criteria for the Stiffness of a System Gear's Method for Integrating Stiff Systems Suggestions for Choosing among the Methods Boundary Value Problems for Ordinary Differential Equations Statement of the Problem Reduction of Boundary Value Problems to Initial Value Problems Boundary Value Problems for Nonlinear Differential Equations of Second Order Boundary Value Problems for Systems of Differential Equations of First Order The Multiple Shooting Method Difference Methods The Ordinary Difference Method Higher Order Difference Methods Iterative Solution of Linear Systems for Special Boundary Value Problems Linear Eigenvalue Problems Appendix: ANSI C Functions Bibliography Literature for Other Topics - Numerical Treatment of Partial Differential Equations - Finite Element Method Index

Get This Torrent

Engeln-Müllges G., Uhlig F. Numerical Algorithms with C 1996.pdf 34.5 MB

Details for: Engeln-Müllges G., Uhlig F. Numerical Algorithms with C 1996

engeln m uuml llges g uhlig f numerical algorithms c 1996

Similar Posts:

Details for: Engeln-M&uuml;llges G., Uhlig F. Numerical Algorithms with C 1996

engeln m uuml llges g uhlig f numerical algorithms c 1996

Similar Posts:

Details for: Engeln-Müllges G., Uhlig F. Numerical Algorithms with C 1996