代码搜索：Definite

找到约 349 项符合「Definite」的源代码

代码结果 349
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m romberg.m

function [rn, r1] = Romberg(fun, a, b, n, varargin) % Numerical approximation rn of the definite integral from a to b % that is obtained with the aid of Romberg's method with n rows % and n c
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m specnd.m

function p = specnd(S,minsep); % SPECND : Spectral nested dissection ordering. % % p = specnd(S,minsep). Nested dissection ordering of S. % For a symmetric positive definite matrix S, this returns %
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m metisnd.m

function p = metisnd(S); % METISND : Metis nested dissection ordering. % % p = metisnd(S): Nested dissection ordering of S. % For a symmetric positive definite matrix S, this returns % a nested disse
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m quad2.m

function ci = quad2(y,x) % Function computes the numerical approximation to the definite % integral y dx (corresponding to sum) % x abscissas % y ordinates % If only one input argument is gi
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m quad2.m

function ci = quad2(y,x) % Function computes the numerical approximation to the definite % integral y dx (corresponding to sum) % x abscissas % y ordinates % If only one input argument is gi
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m invwishirnd.m

% INVWISHIRND - Inverse Wishart Random Matrix % Copyright (c) 1998, Harvard University. Full copyright in the file Copyright % % [IW] = invwishirnd(S,d) % % S = p x p symmetric, postitive definite
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m invwishirnd.m

% INVWISHIRND - Inverse Wishart Random Matrix % Copyright (c) 1998, Harvard University. Full copyright in the file Copyright % % [IW] = invwishirnd(S,d) % % S = p x p symmetric, postitive definite
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m cgsolve.m

% cgsolve.m % % Solve a symmetric positive definite system Ax = b via conjugate gradients. % % Usage: [x, res, iter] = cgsolve(A, b, tol, maxiter, verbose) % % A - Either an NxN matrix, or a function
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c alg066.c

/* * CHOLESKI'S ALGORITHM 6.6 * * To factor the positive definite n by n matrix A into LL**T, * where L is lower triangular. * * INPUT: the dimension n; entries A(I,J), 1
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m testchol.m

% % testchol.m % % % Use the Cholesky decomposition decomposition % to solve a linear system with symmetric positive % definite matrix. % % A = [ 16 4 8 4 4 10 8 4 8 8 12 10
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