Numerical Recipes in C
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1 2008 AGI-Information Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. Numerical Recipes in C The Art of Scientific Computing Second Edition William H. Press Harvard-Smithsonian Center for Astrophysics Saul A. Teukolsky Department of Physics, Cornell University William T. Vetterling Polaroid Corporation Brian P. Flannery EXXON Research and Engineering Company CAMBRIDGE UNIVERSITY PRESS
2 Contents Preface to the Second Edition Preface to the First Edition Legal Matters Computer Programs by Chapter and Section xi xiv xvi xix Preliminaries Introduction Program Organization and Control Structures Some C Conventions for Scientific Computing Error, Accuracy, and Stability 28 Solution of Linear Algebraic Equations Introduction Gauss-Jordan Elimination Gaussian Elimination with Backsubstitution LU Decomposition and Its Applications Tridiagonal and Band Diagonal Systems of Equations Iterative Improvement of a Solution to Linear Equations Singular Value Decomposition Sparse Linear Systems Vandermonde Matrices and Toeplitz Matrices Cholesky Decomposition QR Decomposition Is Matrix Inversion an N 3 Process? 102 Interpolation and Extrapolation Introduction Polynomial Interpolation and Extrapolation Rational Function Interpolation and Extrapolation Cubic Spline Interpolation How to Search an Ordered Table Coefficients of the Interpolating Polynomial Interpolation in Two or More Dimensions 123
3 vi Contents 4 Integration of Functions Introduction Classical Formulas for Equally Spaced Abscissas Elementary Algorithms Romberg Integration Improper Integrals Gaussian Quadratures and Orthogonal Polynomials Multidimensional Integrals Evaluation of Functions Introduction Series and Their Convergence Evaluation of Continued Fractions Polynomials and Rational Functions Complex Arithmetic Recurrence Relations and Clenshaw's Recurrence Formula Quadratic and Cubic Equations Numerical Derivatives Chebyshev Approximation Derivatives or Integrals of a Chebyshev-approximated Function Polynomial Approximation from Chebyshev Coefficients Economization of Power Series Pade Approximants Rational Chebyshev Approximation * Evaluation of Functions by Path Integration Special Functions Introduction Gamma Function, Beta Function, Factorials, Binomial Coefficients Incomplete Gamma Function, Error Function, Chi-Square Probability Function, Cumulative Poisson Function ' Exponential Integrals Incomplete Beta Function, Student's Distribution, F-Distribution, Cumulative Binomial Distribution Bessel Functions of Integer Order Modified Bessel Functions of Integer Order Bessel Functions of Fractional Order, Airy Functions, Spherical <* Bessel Functions Spherical Harmonics Fresnel Integrals, Cosine and Sine Integrals Dawson's Integral Elliptic Integrals and Jacobian Elliptic Functions Hypergeometric Functions Random Numbers Introduction Uniform Deviates 275
4 Contents vii 7.2 Transformation Method: Exponential and Normal Deviates 28J 7.3 Rejection Method: Gamma, Poisson, Binomial Deviates Generation of Random Bits Random Sequences Based on Data Encryption Simple Monte Carlo Integration Quasi- (that is, Sub-) Random Sequences Adaptive and Recursive Monte Carlo Methods Sorting Introduction Straight Insertion and Shell's Method Quicksort Heapsort Indexing and Ranking Selecting the Mth Largest Determination of Equivalence Classes Root Finding and Nonlinear Sets of Equations Introduction Bracketing and Bisection Secant Method, False Position Method, and Ridders' Method Van Wijngaarden-Dekker-Brent Method Newton-Raphson Method Using Derivative Roots of Polynomials Newton-Raphson Method for Nonlinear Systems of Equations Globally Convergent Methods for Nonlinear Systems of Equations Minimization or Maximization of Functions Introduction Golden Section Search in One Dimension Parabolic Interpolation and Brent's Method in One Dimension One-Dimensional Search with First Derivatives Downhill Simplex Method in Multidimensions Direction Set (Powell's) Methods in Multidimensions Conjugate Gradient Methods in Multidimensions Variable Metric Methods in Multidimensions Linear Programming and the Simplex Method 430 > 10.9 Simulated Annealing Methods Eigensystems Introduction Jacobi Transformations of a Symmetric Matrix Reduction of a SymmetricMatrix to Tridiagonal Form: Givens and Householder Reductions Eigenvalues and Eigenvectors of a Tridiagonal Matrix Hermitian Matrices Reduction of a General Matrix to Hessenberg Form 482
5 viii Contents 11.6 The QR Algorithm for Real Hessenberg Matrices Improving Eigenvalues and/or Finding Eigenvectors by Inverse Iteration Fast Fourier Transform Introduction Fourier Transform of Discretely Sampled Data Fast Fourier Transform (FFT) FFT of Real Functions, Sine and Cosine Transforms FFT in Two or More Dimensions Fourier Transforms of Real Data in Two and Three Dimensions External Storage or Memory-Local FFTs Fourier and Spectral Applications Introduction Convolution and Deconvolution Using the FFT Correlation and Autocorrelation Using the FFT Optimal (Wiener) Filtering with the FFT Power Spectrum Estimation Using the FFT Digital Filtering in the Time Domain Linear Prediction and Linear Predictive Coding Power Spectrum Estimation by the Maximum Entropy (All Poles) Method c Spectral Analysis of Unevenly Sampled Data * Computing Fourier Integrals Using the FFT Wavelet Transforms Numerical Use of the Sampling Theorem Statistical Description of Data Introduction Moments of a Distribution: Mean,-Variance, Skewness, and So Forth Do Two Distributions Have the Same Means or Variances? Are Two Distributions Different? Contingency Table Analysis of Two Distributions Linear Correlation Nonparametric or Rank Correlation Do Two-Dimensional Distributions Differ? Savitzky-Golay Smoothing Filters Modeling of Data Introduction Least Squares as a Maximum Likelihood Estimator Fitting Data to a Straight Line Straight-Line Data with Errors in Both Coordinates General Linear Least Squares Nonlinear Models 681
6 Contents ix 15.6 Confidence Limits on Estimated Model Parameters Robust Estimation Integration of Ordinary Differential Equations Introduction Runge-Kutta Method Adaptive Stepsize Control for Runge-Kutta Modified Midpoint Method Richardson Extrapolation and the Bulirsch-Stoer Method Second-Order Conservative Equations Stiff Sets of Equations Multistep, Multivalue, and Predictor-Corrector Methods Two Point Boundary Value Problems Introduction The Shooting Method Shooting to a Fitting Point Relaxation Methods A Worked Example: Spheroidal Harmonics Automated Allocation of Mesh Points Handling Internal Boundary Conditions or Singular Points Integral Equations and Inverse Theory Introduction Fredholm Equations of the Second Kind Volterra Equations Integral Equations with Singular Kernels Inverse Problems and the Use of A Priori Information Linear Regularization Methods Backus-Gilbert Method Maximum Entropy Image Restoration Partial Differential Equations Introduction Flux-Conservative Initial Value Problems Diffusive Initial Value Problems Initial Value Problems in Multidimensions Fourier and Cyclic Reduction Methods for Boundary Value Problems Relaxation Methods for Boundary Value Problems Multigrid Methods for Boundary Value Problems Less-Numerical Algorithms Introduction Diagnosing Machine Parameters Gray Codes 894
7 x Contents 20.3 Cyclic Redundancy and Other Checksums 20.4 Huffman Coding and Compression of Data 20.5 Arithmetic Coding 20.6 Arithmetic at Arbitrary Precision References Appendix A: Table of Prototype Declarations Appendix B: Utility Routines Appendix C: Complex Arithmetic Index of Programs and Dependencies General Index
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