代码搜索：Probability
找到约 4,670 项符合「Probability」的源代码
代码结果 4,670
www.eeworm.com/read/463748/7175965
m bdt_f531.m
% MATLAB script that generates the probability of error versus the signal-to-noise ratio.
initial_snr=0;
final_snr=12;
snr_step=0.75;
tolerance=eps; % tolerance used for the integration
www.eeworm.com/read/461382/7228254
m simulateugi.m
function sim_state = SimulateUGI( sim_param, sim_state, code_param )
% SimulateUGI simulates the information outage probability of 1 or 2-D
% modulation with an unconstrained Gaussian input (UGI)
%
www.eeworm.com/read/461382/7228256
m simulateoutage.m
function sim_state = SimulateOutage( sim_param, sim_state, code_param )
% SimulateOutage runs a single information outage probability simulation.
%
% The calling syntax is:
% sim_state = Simul
www.eeworm.com/read/451547/7461931
m dd_normc.m
%DD_NORMC Normalize the output of a oc-classifier
%
% B = DD_NORMC(A)
% B = A*W*DD_NORMC
% W = DD_NORMC
%
% Normalize the mapped dataset A to standard 'posterior probability'
% est
www.eeworm.com/read/445831/7589514
m bdt_f531.m
% MATLAB script that generates the probability of error versus the signal-to-noise ratio.
initial_snr=0;
final_snr=12;
snr_step=0.75;
tolerance=eps; % tolerance used for the integration
www.eeworm.com/read/439811/7701509
m bdt_f531.m
% MATLAB script that generates the probability of error versus the signal-to-noise ratio.
initial_snr=0;
final_snr=12;
snr_step=0.75;
tolerance=eps; % tolerance used for the integration
www.eeworm.com/read/197261/8008636
m radiobase.m
ModelType='LOS';
%Separation distance Eexpressed in meet
Dn=5;
switch ModelType
% For line-of-sight
case 'LOS'
% Probability of receiving a multipath
for i=1:14
PTk(i)=1-i*7.8/36
www.eeworm.com/read/244937/12831088
m bdt_f531.m
% MATLAB script that generates the probability of error versus the signal-to-noise ratio.
initial_snr=0;
final_snr=12;
snr_step=0.75;
tolerance=eps; % tolerance used for the integration
www.eeworm.com/read/143706/12849700
m histp.m
function h = histp(x, xmin, xmax, nbins)
%HISTP Histogram estimate of 1-dimensional probability distribution.
%
% Description
%
% HISTP(X, XMIN, XMAX, NBINS) takes a column vector X of data values
%
www.eeworm.com/read/140851/13059059
m histp.m
function h = histp(x, xmin, xmax, nbins)
%HISTP Histogram estimate of 1-dimensional probability distribution.
%
% Description
%
% HISTP(X, XMIN, XMAX, NBINS) takes a column vector X of data valu