代码搜索：fprintf

找到约 10,000 项符合「fprintf」的源代码

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c alg091.c

/* * POWER METHOD ALGORITHM 9.1 * * To approximate the dominant eigenvalue and an associated * eigenvector of the n by n matrix A given a nonzero vector x: * * INPUT: Dimension n; matr
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c alg061.c

/* * GAUSSIAN ELIMINATION WITH BACKWARD SUBSTITUTION ALGOTITHM 6.1 * * To solve the n by n linear system * * E1: A[1,1] X[1] + A[1,2] X[2] +...+ A[1,n] X[n] = A[1,n+1] * E2: A[2,1] X[1
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c alg064.c

/* * DIRECT FACTORIZATION ALGORITHM 6.4 * * To factor the n by n matrix A = (A(I,J)) into the product of the * lower triangular matrix L = (L(I,J)) and U = (U(I,J)), that is * A = LU, whe
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c alg062.c

/* * GAUSSIAN ELIMINATION WITH PARTIAL PIVOTING ALGORITHM 6.2 * * To solve the n by n linear system * * E1: A[1,1] X[1] + A[1,2] X[2] +...+ A[1,n] X[n] = A[1,n+1] * E2: A[2,1] X[1] + A
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c alg092.c

/* * SYMMETRIC POWER METHOD ALGORITHM 9.2 * * To approximate the dominant eigenvalue and an associated * eigenvector of the n by n symmetric matrix A given a nonzero vector x: * * INPUT:
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c alg075.c

/* * CONJUGATE GRADIENT ALGORITHM 7.5 * * To solve Ax = b given the preconditioning matrix C inverse and * an initial approximation x(0): * * INPUT: the number of equations and unknown
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c alg073.c

/* * SOR ALGORITHM 7.3 * * To solve Ax = b given the parameter w and an initial approximation * x(0): * * INPUT: the number of equations and unknowns n; the entries * A(I,J
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c alg083.c

/* * FAST FOURIER TRANSFORM ALGORITHM 8.3 * * To compute the coefficients in the discrete approximation * for the data (x(J),y(J)), 0
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c alg102.c

/* * BROYDEN ALGORITHM 10.2 * * To approximate the solution of the nonlinear system F(X) = 0 * given an initial approximation X. * * INPUT: Number n of equations and unknowns; initial
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c alg094.c

/* * WIELANDT'S DEFLATION ALGORITHM 9.4 * * To approximate the second most dominant eigenvalue and an * associated eigenvector of the n by n matrix A given an * approximation LAMBDA to th
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