代码搜索：Multi
找到约 10,000 项符合「Multi」的源代码
代码结果 10,000
www.eeworm.com/read/450547/7481889
gif multi-1.gif
www.eeworm.com/read/447973/7542768
measure4multi
nmc=11
nz=2
kmax=93
run number , frame , sample interval , measurements:
1 1 1.709471 186.698339 253.722301
1 2 1.709471 487.482449 613.161853
1 3 1.709471 988.073293 1122.339135
1 4 1.
www.eeworm.com/read/447973/7542851
system4multi
nmc=11
nx=6
kmax=93
run number , frame , sample interval , truth:
1 1 1.709471 186.445110 118.112128 67.943915 253.390071 168.877232 50.131071
1 2 1.709471 487.596135 234.220208 67.920458 61
www.eeworm.com/read/446050/7586463
m multi_gp.m
function x=multi_gp(m,C)
% MULTI_GP 产生均值向量为m（列向量）和协方差矩阵为C的多元高斯随机过程.
N=length(m);
for i=1:N,
y(i) =gngauss;
end;
y=y.';
x=sqrtm(C)*y+m;
www.eeworm.com/read/446050/7586464
asv multi_gp.asv
function [x]=multi_gp(m,C)
% MULTI_GP 产生均值向量为m（列向量）和协方差矩阵为C的多元高斯随机过程.
N=length(m);
for i=1:N,
y(i) =gngauss;
end;
y=y.';
x=sqrtm(C)*y+m;
www.eeworm.com/read/445827/7589601
m multi_gp.m
function [x] = multi_gp(m,C)
% [x]=multi_gp(m,C)
% MULTI_GP generates a multivariate Gaussian random
% process with mean vector m (column vector) and covariance matrix C.
N=length(m);
for
www.eeworm.com/read/442444/7651680
m multi_gp.m
function [x] = multi_gp(m,C)
% [x]=multi_gp(m,C)
% MULTI_GP generates a multivariate Gaussian random
% process with mean vector m (column vector) and covariance matrix C.
N=length(m);
for
www.eeworm.com/read/441245/7673029
m multi_labeling.m
%MULTI_LABELING Info on the PRTools multiple labeling system.
%
% This is not a command, just an information file.
%
% In the PRTools datasets the data is stored together with the class labels
%
www.eeworm.com/read/440123/7693839
vhd vgacore_multi.vhd
------------------------------------------------------------------
-- Copyright (c) 1995-2005 Xilinx, Inc.
-- All Right Reserved.
------------------------------------------------------------------
--
www.eeworm.com/read/439811/7701540
m multi_gp.m
function [x] = multi_gp(m,C)
% [x]=multi_gp(m,C)
% MULTI_GP generates a multivariate Gaussian random
% process with mean vector m (column vector) and covariance matrix C.
N=length(m);
for