代码搜索：fprintf
找到约 10,000 项符合「fprintf」的源代码
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www.eeworm.com/read/386253/8759993
m alg046.m
% GAUSSIAN TRIPLE INTEGRAL ALGORITHM 4.6
%
% To approximate I = triple integral ( ( f(x,y,z) dz dy dx ) ) with
% limits of integration from a to b for x, from c(x) to d(x) for y, and
% from
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m alg062.m
% 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(2,2) X(2) +
www.eeworm.com/read/386253/8760007
m alg073.m
% 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), 1
www.eeworm.com/read/386253/8760022
m alg104.m
% CONTINUATION METHOD FOR SYSTEMS ALGORITHM 10.1
%
% To approximate the solution of the nonlinear system F(X)=0 given
% an initial approximation X:
%
% INPUT: Number n of equations and unknowns
www.eeworm.com/read/386253/8760025
m alg123.m
% CRANK-NICOLSON ALGORITHM 12.3
%
% To approximate the solution of the parabolic partial-differential
% equation subject to the boundary conditions
% u(0,t) = u(l,t) = 0, 0 < t < T = ma
www.eeworm.com/read/386253/8760031
m alg034.m
% NATURAL CUBIC SPLINE ALGORITHM 3.4 %
% To construct the cubic spline interpolant S for the function f,
% defined at the numbers x(0) < x(1) < ... < x(n), sat
www.eeworm.com/read/386253/8760039
m alg082.m
% CHEBYSHEV RATIONAL APPROXIMATION ALGORITHM 8.2
%
% To obtain the rational approximation
%
% rT(x) = (p0*T0 + p1*T1 +...+ pn*Tn) / (q0*T0 + q1*T1 +...+ qm*Tm)
%
% for a given function f(x):
%
www.eeworm.com/read/386253/8760041
m alg124.m
% WAVE EQUATION FINITE-DIFFERENCE ALGORITHM 12.4
%
% To approximate the solution to the wave equation:
% subject to the boundary conditions
% u(0,t) = u(l,t) = 0, 0 < t < T = max t
%
www.eeworm.com/read/386253/8760049
m alg057.m
% RUNGE-KUTTA FOR SYSTEMS OF DIFFERENTIAL EQUATIONS ALGORITHM 5.7
%
% TO APPROXIMATE THE SOLUTION OF THE MTH-ORDER SYSTEM OF FIRST-
% ORDER INITIAL-VALUE PROBLEMS
% UJ' = FJ( T, U1, U2,
www.eeworm.com/read/386253/8760061
m alg072.m
% GAUSS-SEIDEL ITERATIVE TECHNIQUE ALGORITHM 7.2
%
% To solve Ax = b given an initial approximation x(0).
%
% INPUT: the number of equations and unknowns n; the entries
% A(I,J), 1