代码搜索：deviation
找到约 1,443 项符合「deviation」的源代码
代码结果 1,443
www.eeworm.com/read/463748/7176073
m gngauss.m
function [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(sgma)
% [gsrv1,gsrv2]=gngauss
% GNGAUSS generates two independent Gaussian random variables with me
www.eeworm.com/read/463748/7176119
m gngauss.m
function [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(sgma)
% [gsrv1,gsrv2]=gngauss
% GNGAUSS generates two independent Gaussian random variables with me
www.eeworm.com/read/462323/7202780
m gngauss.m
function [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(sgma)
% [gsrv1,gsrv2]=gngauss
% GNGAUSS generates two independent Gaussian random variables with me
www.eeworm.com/read/462318/7202827
m gngauss.m
function [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(sgma)
% [gsrv1,gsrv2]=gngauss
% GNGAUSS generates two independent Gaussian random variables with me
www.eeworm.com/read/461264/7230303
readme robust.readme
Robust Statistics Procudures July 2003
In 1995, Henry Freudenriech (Hughes STX) developed a library of robust
statistics procedures in IDL (called ROBLIB), which has been stor
www.eeworm.com/read/460435/7250469
m gendatl.m
%GENDATL Generation of Lithuanian classes
%
% A = GENDATL(N,S)
%
% INPUT
% N Number of objects per class (optional; default: [50 50])
% S Standard deviation for the data generation (optional; d
www.eeworm.com/read/460435/7251179
m gendatsin.m
%GENREGSIN Generate sinusoidal regression data
%
% X = GENDATSIN(N,SIGMA)
%
% INPUT
% N Number of objects to generate
% SIGMA Standard deviation of the noise
%
% OUTPUT
% X Reg
www.eeworm.com/read/456469/7348875
m reinforcementlearning.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Q learning of single agent move in N rooms
% Matlab Code companion of
% Q Learning by Example
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
www.eeworm.com/read/456354/7351284
m gngauss.m
function [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(sgma)
% [gsrv1,gsrv2]=gngauss
% GNGAUSS generates two independent Gaussian random variables with mean
%
www.eeworm.com/read/456354/7351301
m gngauss.m
function [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(m,sgma)
% [gsrv1,gsrv2]=gngauss(sgma)
% [gsrv1,gsrv2]=gngauss
% GNGAUSS generates two independent Gaussian random variables with mean
%