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/286900/8738140
m plot_gaussian.m
function plot_gaussian(number_clusters, power, AOA_deg, sigma_deg, ...
delta_phi_deg, plot_number, colour)
% plot_gaussian(number_clusters, power, AOA_deg, sigma_deg,
% delta_
www.eeworm.com/read/286900/8738156
m normalisation_gaussian.m
function [Q, sigma_deg] = normalisation_gaussian(number_clusters, ...
power_lin, AS_deg, delta_phi_deg)
% [Q, sigma_deg] = normalisation_gaussian(number_clusters,
% power_lin,
www.eeworm.com/read/286900/8738171
m rxx_gaussian.m
function result = Rxx_gaussian(d_norm,phi_0_deg,sigma_deg,delta_phi_deg)
% result = Rxx_gaussian(d_norm,phi_0_deg,sigma_deg,delta_phi_deg)
%
% Computes the correlation of the real and imaginary par
www.eeworm.com/read/428167/8885966
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
www.eeworm.com/read/383944/8909496
cpp gaussian_channel.cpp
#include "LDPC_head.h"
#include
code *Gaussian_channel(code *codewords,double n0)
{
unsigned int i;
double u1,u0;
double gaussnoise;
for(i=0;ilength;i++)
{
www.eeworm.com/read/427909/8912949
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
www.eeworm.com/read/427909/8912966
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/427909/8913038
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
www.eeworm.com/read/427909/8913128
m marginalize_gaussian.m
function [muX, SXX] = marginalize_gaussian(mu, Sigma, X, Y, ns)
% MARGINALIZE_GAUSSIAN Compute Pr(X) from Pr(X,Y) where X and Y are jointly Gaussian.
% [muX, SXX] = marginalize_gaussian(mu, Sigma, X
www.eeworm.com/read/283824/8986574
m gaussian_filt.m
% makes zero-mean gaussian filter by taking sz samples from gaussian distribution
% sz is a vector with dimensions of the filter
sz = 5;
x = -2:2;
sigma = 1;
% 1D gaussian
g1 = exp(-x.^2/2);