代码搜索:solving
找到约 630 项符合「solving」的源代码
代码结果 630
www.eeworm.com/read/192391/5157289
lua bisect.lua
-- bisection method for solving non-linear equations
delta=1e-6 -- tolerance
function bisect(f,a,b,fa,fb)
local c=(a+b)/2
io.write(n," c=",c," a=",a," b=",b,"\n")
if c==a or c==b or math.a
www.eeworm.com/read/192080/5160176
lua bisect.lua
-- bisection method for solving non-linear equations
delta=1e-6 -- tolerance
function bisect(f,a,b,fa,fb)
local c=(a+b)/2
io.write(n," c=",c," a=",a," b=",b,"\n")
if c==a or c==b or math.a
www.eeworm.com/read/460330/7253780
m srung5.m
% Function Subprogram srung3.m
%
% Solving the nonlinear parts of the coupled differential
% equations using a fourth-order Runge-Kutta algorithm
%
function y = srung3(rho1,rho2,sig1,sig2,a,b,h
www.eeworm.com/read/264154/11327578
m xw_ga_ann19.m
%Genetic algorithm for solving simple optimization problem
%f(x)=x1^2+x2^2,-5
www.eeworm.com/read/256950/11963218
m xw_ga_ann19.m
%Genetic algorithm for solving simple optimization problem
%f(x)=x1^2+x2^2,-5
www.eeworm.com/read/290224/8495206
lua bisect.lua
-- bisection method for solving non-linear equations
delta=1e-6 -- tolerance
function bisect(f,a,b,fa,fb)
local c=(a+b)/2
io.write(n," c=",c," a=",a," b=",b,"\n")
if c==a or c==b or math.abs(a-b)
www.eeworm.com/read/430698/8733515
txt md5碰撞的程序(c源代码).txt
根据王小云教授的算法写的MD5碰撞的程序[c源代码]
/* MD5 Collision Generator by Patrick Stach
* Implementation of paper by Xiaoyun Wang, et all.
*
* A few optimizations to make the solving method
www.eeworm.com/read/373220/9468815
m frmnts.m
function [F1,F2, F3]=frmnts(a,srat)
% The formants are computed by solving for the roots of the LPC polynomial
%
% Copyright (c) 1998 by Philipos C. Loizou
%
global f1p f2p f3p
const=s
www.eeworm.com/read/419627/10853055
lua bisect.lua
-- bisection method for solving non-linear equations
delta=1e-6 -- tolerance
function bisect(f,a,b,fa,fb)
local c=(a+b)/2
io.write(n," c=",c," a=",a," b=",b,"\n")
if c==a or c==b or math.abs(a-b)
www.eeworm.com/read/417661/10981144
c sparsesvd.c
/*
Finds a sparse rank-one approximation to a given symmetric matrix A, by solving the SDP
min_X lambda_max(A+X) : X = X', abs(X(i,j))