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Numerical Recipes Example Book C++ 2nd Edition

Numerical Recipes Example Book C++ 2nd EditionHere are some highlights of the new material in this ebook:
 a new chapter on integral equations and inverse methods
 a detailed treatment of multigrid methods for solving elliptic partial differential equations
 routines for band diagonal linear systems
 improved routines for linear algebra on sparse matrices
 Cholesky and QR decomposition
 orthogonal polynomials and Gaussian quadratures for arbitrary weight functions
 methods for calculating numerical derivatives
 Pad´e approximants, and rational Chebyshev approximation
 Bessel functions, and modified Bessel functions, of fractional order; and several other new special functions
 improved random number routines
 quasi-random sequences
 routines for adaptive and recursive Monte Carlo integration in highdimensional spaces
 globally convergent methods for sets of nonlinear equations
 simulated annealing minimization for continuous control spaces
 fast Fourier transform (FFT) for real data in two and three dimensions
 fast Fourier transform (FFT) using external storage
 improved fast cosine transform routines
 wavelet transforms
 Fourier integrals with upper and lower limits
 spectral analysis on unevenly sampled data
 Savitzky-Golay smoothing filters
 fitting straight line data with errors in both coordinates
 a two-dimensional Kolmogorov-Smirnoff test
 the statistical bootstrap method
 embedded Runge-Kutta-Fehlberg methods for differential equations
 high-order methods for stiff differential equations
 a new chapter on “less-numerical” algorithms, including Huffman and arithmetic coding, arbitrary precision arithmetic, and several other topics.

1 Preliminaries
2 Solution of Linear Algebraic Equations
3 Interpolation and Extrapolation
4 Integration of Functions
5 Evaluation of Functions
6 Special Functions
7 Random Numbers
8 Sorting
9 Root Finding and Nonlinear Sets of Equations
10 Minimization or Maximization of Functions
11 Eigensystems
12 Fast Fourier Transform
13 Fourier and Spectral Applications
14 Statistical Description of Data
15 Modeling of Data
16 Integration of Ordinary Differential Equations
17 Two Point Boundary Value Problems
18 Integral Equations and Inverse Theory
19 Partial Differential Equations
20 Less-Numerical Algorithms
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