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/447716/7546243
m plot_gaussian.m
function plot_gaussian(number_clusters, power, AOA_deg, sigma_deg, ...
delta_phi_deg, plot_number)
% plot_gaussian(number_clusters, power, AOA_deg, sigma_deg,
% delta_phi_deg,
www.eeworm.com/read/447716/7546253
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/447716/7546263
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/444270/7615421
m fit_gaussian.m
function [mu, sigma] = fit_gaussian(x,class)
N = max(class);
mu = zeros(N,size(x,2));
sigma = zeros(size(x,2),size(x,2),N);
for i=1:N,
mu(i,:) = mean(x(class==i,:));
sigma(:,:,i) = c
www.eeworm.com/read/444270/7615422
m ml_gaussian.m
function index = ML_gaussian(x,mu,sigma)
% function index = ML_gaussian(x,mu,sigma)
% x is a vector drawn from some multivariate gaussian
% mu(i,:) is the mean of the ith Gaussian
% sigma(:,:,i) i
www.eeworm.com/read/443608/7630272
m cumulative_gaussian.m
%CUMULATIVE_GAUSSIAN: the integral of the Gaussian distribution, which
% gives the probability that a variate will assume a value
www.eeworm.com/read/442822/7644327
m cumulative_gaussian.m
%CUMULATIVE_GAUSSIAN: the integral of the Gaussian distribution, which
% gives the probability that a variate will assume a value
www.eeworm.com/read/439361/7711577
m gaussian_derivatives.m
%
% FUNCTION 7.2 : "cp0702_Gaussian_derivatives"
%
% Analysis of waveforms of the Gaussian pulse and its first
% 15 derivatives
%
% The pulse amplitude is set to 'A'
% 'smp' samples of the Gaus
www.eeworm.com/read/436446/7769699
m gaussian_noise.m
function x = gaussian_noise(P)
%-------------------------------------------------------
% University of Zaragoza
% Centro Politecnico Superior
% Robotics and Real Time Group
% Authors: J. Neira,
www.eeworm.com/read/299736/7836204
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