Computer Programs by Chapter and Section xxiii 9.6 mnewt Newton's method for systems of equations 9.7 Insrch search along a line,used by newt 9.7 newt globally convergent multi-dimensional Newton's method 9.7 fdjac finite-difference Jacobian,used by newt 9.7 fmin norm of a vector function,used by newt 9.7 broydn secant method for systems of equations 10.1 mnbrak bracket the minimum of a function 10.1 golden find minimum of a function by golden section search http://www.nr read able files Permission is opyright(C Sample page 10.2 brent find minimum of a function by Brent's method 10.3 dbrent find minimum of a function using derivative information 83 10.4 amoeba minimize in N-dimensions by downhill simplex method granted for 10.4 amotry evaluate a trial point,used by amoeba 10.5 powell minimize in N-dimensions by Powell's method 11-800-872 (including this one) 10.5 linmin minimum of a function along a ray in N-dimensions 10.5 fidim function used by linmin 7423 1988-1992 by Cambridge University Press.Programs Copyright(C) tusers to make one paper from NUMERICAL RECIPES IN 10.6 frprmn minimize in N-dimensions by conjugate gradient 10.6 dlinmin minimum of a function along a ray using derivatives 10.6 df1dim function used by dlinmin 10.7 dfpmin minimize in N-dimensions by variable metric method (North America to any server computer,is strictly prohibited. THE 10.8 simplx linear programming maximization of a linear function 10.8 simp1 linear programming,used by simplx only). ART 10.8 simp2 linear programming,used by simplx 10.8 simp3 linear programming,used by simplx send copy for their 10.9 anneal traveling salesman problem by simulated annealing 10.9 revcst cost of a reversal,used by anneal email 10.9 reverse do a reversal,used by anneal 10.9 trncst cost of a transposition,used by anneal 10.9 trnspt do a transposition,used by anneal 10.9 metrop Metropolis algorithm.used by anneal 10.9 amebsa simulated annealing in continuous spaces 10.9 amotsa evaluate a trial point,used by amebsa OF SCIENTIFIC COMPUTING(ISBN 0-521-43108-5) 11.1 jacobi eigenvalues and eigenvectors of a symmetric matrix To order Numerical Recipes books or personal use.Further reproduction,or 1988-1992 by Numerical Recipes 11.1 eigsrt eigenvectors,sorts into order by eigenvalue 11.2 tred2 Householder reduction of a real,symmetric matrix 11.3 tqli eigensolution of a symmetric tridiagonal matrix 11.5 balanc balance a nonsymmetric matrix Software. 11.5 elmhes reduce a general matrix to Hessenberg form @cambridge.org(outside North America). 11.6 hgr eigenvalues of a Hessenberg matrix 12.2 four1 fast Fourier transform (FFT)in one dimension 12.3 twofft fast Fourier transform of two real functions 12.3 realft fast Fourier transform of a single real function 12.3 sinft fast sine transform 12.3 cosft1 fast cosine transform with endpoints 12.3 cosft2 "staggered"fast cosine transformComputer Programs by Chapter and Section xxiii Permission is granted for internet users to make one paper copy for their own personal use. Further reproduction, or any copyin Copyright (C) 1988-1992 by Cambridge University Press. Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5) g of machine￾readable files (including this one) to any server computer, is strictly prohibited. To order Numerical Recipes books or CDROMs, visit website http://www.nr.com or call 1-800-872-7423 (North America only), or send email to directcustserv@cambridge.org (outside North America). 9.6 mnewt Newton’s method for systems of equations 9.7 lnsrch search along a line, used by newt 9.7 newt globally convergent multi-dimensional Newton’s method 9.7 fdjac finite-difference Jacobian, used by newt 9.7 fmin norm of a vector function, used by newt 9.7 broydn secant method for systems of equations 10.1 mnbrak bracket the minimum of a function 10.1 golden find minimum of a function by golden section search 10.2 brent find minimum of a function by Brent’s method 10.3 dbrent find minimum of a function using derivative information 10.4 amoeba minimize in N-dimensions by downhill simplex method 10.4 amotry evaluate a trial point, used by amoeba 10.5 powell minimize in N-dimensions by Powell’s method 10.5 linmin minimum of a function along a ray in N-dimensions 10.5 f1dim function used by linmin 10.6 frprmn minimize in N-dimensions by conjugate gradient 10.6 dlinmin minimum of a function along a ray using derivatives 10.6 df1dim function used by dlinmin 10.7 dfpmin minimize in N-dimensions by variable metric method 10.8 simplx linear programming maximization of a linear function 10.8 simp1 linear programming, used by simplx 10.8 simp2 linear programming, used by simplx 10.8 simp3 linear programming, used by simplx 10.9 anneal traveling salesman problem by simulated annealing 10.9 revcst cost of a reversal, used by anneal 10.9 reverse do a reversal, used by anneal 10.9 trncst cost of a transposition, used by anneal 10.9 trnspt do a transposition, used by anneal 10.9 metrop Metropolis algorithm, used by anneal 10.9 amebsa simulated annealing in continuous spaces 10.9 amotsa evaluate a trial point, used by amebsa 11.1 jacobi eigenvalues and eigenvectors of a symmetric matrix 11.1 eigsrt eigenvectors, sorts into order by eigenvalue 11.2 tred2 Householder reduction of a real, symmetric matrix 11.3 tqli eigensolution of a symmetric tridiagonal matrix 11.5 balanc balance a nonsymmetric matrix 11.5 elmhes reduce a general matrix to Hessenberg form 11.6 hqr eigenvalues of a Hessenberg matrix 12.2 four1 fast Fourier transform (FFT) in one dimension 12.3 twofft fast Fourier transform of two real functions 12.3 realft fast Fourier transform of a single real function 12.3 sinft fast sine transform 12.3 cosft1 fast cosine transform with endpoints 12.3 cosft2 “staggered” fast cosine transform