代码搜索：gaussian
找到约 7,040 项符合「gaussian」的源代码
代码结果 7,040
www.eeworm.com/read/299736/7836208
m sample_gaussian.m
function M = sample_gaussian(mu, Sigma, N)
% SAMPLE_GAUSSIAN Draw N random row vectors from a Gaussian distribution
% samples = sample_gaussian(mean, cov, N)
if nargin==2
N = 1;
end
% If Y
www.eeworm.com/read/298894/7927145
m gaussian_pulse.m
%
%function p = pulse(t,tau)
%
function p = gaussian_pulse(A,t,alpha)
p = A*exp(-2*pi*(t/alpha).^2);
return
www.eeworm.com/read/397106/8067643
m change_gaussian.m
function change_gaussian
%When the user selects a different Gaussian, change the display to show that Gaussian.
%Used by the manual entry screen.
load synthetic
h = findobj('Tag', 'popNumb
www.eeworm.com/read/333698/12664328
m plot_gaussian.m
function [hh] = plot_gaussian(covar,mu,col,n)
if ~isempty(find(covar-covar == 0))
if size(mu,1) < size(mu,2), mu = mu'; end
if size(covar,1) == 3
theta = (0:1:n-1)'/(n-1)*pi;
www.eeworm.com/read/246573/12718855
m gaussian_elimination.m
function [L,U]=LU(A)
% Gaussian Elimination
Size=size(A);
m=Size(1,1); %计算行数
R=eye(m);%产生单位矩阵，以后用于L
n=Size(1,2);%计算列数
num=1;%设置变换的行数
Z=0;%记录行变换次数
for i=1:m
for k=i:m
if abs(A(i,i
www.eeworm.com/read/331191/12839957
pdf gaussian_game.pdf
www.eeworm.com/read/243898/12908155
m gaussian_prob.m
function p = gaussian_prob(x, m, C, use_log)
% GAUSSIAN_PROB Evaluate a multivariate Gaussian density.
% p = gaussian_prob(X, m, C, use_log)
%
% p(i) = N(X(:,i), m, C) if use_log = 0 (default)
% p(i)
www.eeworm.com/read/243898/12908157
m gaussian_sample.m
function x = gsamp(mu, covar, nsamp)
%GSAMP Sample from a Gaussian distribution.
%
% Description
%
% X = GSAMP(MU, COVAR, NSAMP) generates a sample of size NSAMP from a
% D-dimensional Gaussian distri
www.eeworm.com/read/243896/12908167
m sample_gaussian.m
function M = sample_gaussian(mu, Sigma, N)
% SAMPLE_GAUSSIAN Draw N random row vectors from a Gaussian distribution
% samples = sample_gaussian(mean, cov, N)
if nargin==2
N = 1;
end
% If Y = CX, V
www.eeworm.com/read/140851/13058312
m gaussian_prob.m
function p = gaussian_prob(x, m, C, use_log)
% GAUSSIAN_PROB Evaluate a multivariate Gaussian density.
% p = gaussian_prob(X, m, C)
% p(i) = N(X(:,i), m, C) where C = covariance matrix and each COL