代码搜索:Generates

找到约 10,000 项符合「Generates」的源代码

代码结果 10,000
www.eeworm.com/read/289731/8532115

c alg32.c

#include #include #include #include /* * generates: original array values: 3 5 8 13 21 transform each element by doubling: 6 10 16 26 42 tr
www.eeworm.com/read/289286/8561165

m mmse_mse_calc.m

%Function Declaration: function ms_error=MMSE_MSE_calc(X,H,Y,Rgg,variance); %This function generates mean squared error for the the MMSE estimator.. %EVALUATION OF Hmmse %Hmmse=F*Rgg*inv(Rgy)*Y;
www.eeworm.com/read/288910/8594722

c alg43.c

#include #include #include /* generates: original element sequence: 29 23 20 22 12 17 15 26 51 19 12 23 35 40 stable sort -- default ascending order
www.eeworm.com/read/288910/8594726

c alg38.c

#include #include #include /* generates: original element sequence: 0 1 1 2 3 5 8 13 21 34 sequence after applying remove_if < 10: 13 21 34
www.eeworm.com/read/288910/8594731

c alg45.c

#include #include #include /* generates: original element sequence: 29 23 20 22 17 15 26 51 19 12 35 40 stable_partition on even element: 20 22
www.eeworm.com/read/288910/8594833

c alg32.c

#include #include #include #include /* * generates: original array values: 3 5 8 13 21 transform each element by doubling: 6 10 16 26 42 tr
www.eeworm.com/read/388426/8609924

m sacubic.m

function [ab,vE,E] = sacubic(N); % % Ph.D. Thesis % Leandro Nunes de Castro % October, 1999. % Function generates n-bit binary strings antibody most uniformly % distributed over the search spac
www.eeworm.com/read/388426/8609937

m donuts.m

function S = donuts; % % Ph.D. Thesis % Leandro Nunes de Castro % February, 2000 % Function generates the dataset for the 2-DONUTS problem % % DONUT 1 step = 0.2; t = 0:step:4*pi; l = le
www.eeworm.com/read/388426/8610065

m saml.m

function [ab,vE,E] = saml(N); % % Ph.D. Thesis % Leandro Nunes de Castro % October, 1999. % Function generates n-bit binary strings antibody most uniformly % distributed over the search space
www.eeworm.com/read/288303/8643945

m gaussn.m

function g = gaussn(f0,n) % function gn = gaussn(f0,n) : generates the order n derivative of the % gaussian window, centered at frequency f0 % The wavelet gn is real, but it is its analytic form