代码搜索：Spatial
找到约 1,342 项符合「Spatial」的源代码
代码结果 1,342
www.eeworm.com/read/223514/14636836
m gendata_2tx_sm.m
function gendata_2Tx_SM(permutation,sympf_2Tx,qam)
% Generate original modulation data for 2 Antennas Spatial Multiplex
%sympf_2Tx=6*2;
%qam=16;
% generate raw constellation data for one frame
www.eeworm.com/read/208294/4994149
das natl_prof_bot.cdp.das
Attributes {
ogr_layer_info_1 {
string layer_name normalized;
string spatial_ref WGS84;
string target_container location.profile;
x_field {
string name location.lon;
st
www.eeworm.com/read/252302/4409834
das natl_prof_bot.cdp.das
Attributes {
ogr_layer_info_1 {
string layer_name normalized;
string spatial_ref WGS84;
string target_container location.profile;
x_field {
string name location.lon;
st
www.eeworm.com/read/171369/9759313
m gendata_2tx_sm.m
function gendata_2Tx_SM(permutation,sympf_2Tx,qam)
% Generate original modulation data for 2 Antennas Spatial Multiplex
%sympf_2Tx=6*2;
%qam=16;
% generate raw constellation data for one frame
www.eeworm.com/read/389321/8533544
m display_curv_con.m
% fdct_wrapping_demo_basic.m -- Displays a curvelet both in the spatial and frequency domains.
close all;clear all;
m = 512;
n = 512;
X = zeros(m,n);
addpath('/home/truong/pdfb/CurveLab-2.0/fdct_wr
www.eeworm.com/read/383526/8940050
m scm.m
function [H, delays, full_output]=scm(scmpar,linkpar,antpar,initvalues)
%SCM 3GPP Spatial Channel Model (3GPP TR 25.996)
% H=SCM(SCMPAR,LINKPAR,ANTPAR) is a 5D-array of channel coefficients. For
www.eeworm.com/read/359807/10124078
m scm.m
function [H, delays, full_output]=scm(scmpar,linkpar,antpar,initvalues)
%SCM 3GPP Spatial Channel Model (3GPP TR 25.996)
% H=SCM(SCMPAR,LINKPAR,ANTPAR) is a 5D-array of channel coefficients. For
www.eeworm.com/read/449504/7502843
m sac.m
function results = sac(y,x,W1,W2,info)
% PURPOSE: computes general Spatial Model estimates
% model: y = rho*W1*y + X*b + u, u = lam*W2*u + e
% ---------------------------------------------------
www.eeworm.com/read/449504/7502913
m far_g.m
function results = far_g(y,W,ndraw,nomit,prior)
% PURPOSE: Bayesian estimates for the 1st-order Spatial autoregressive model
% y = rho*W*y + e, e = N(0,sige*V),
% V = diag(v1,
www.eeworm.com/read/449504/7503074
m sar_c.m
function results = sar_c(y,x,W,prior)
% PURPOSE: Bayesian log-marginal posterior for the spatial autoregressive model
% y = rho*W*y + XB + e, e = N(0,sige*In)
% B = N[0,inv(g*X'X)