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sa_fig4_13.m
%Smart Antennas figure 4.13 Blackman weights on a linear array
d=.5;
N=input('what is the number of elements?');
theta=-pi/2:.01:pi/2;
ang=theta*180/pi;
test=blackman(N);
check=mod(N,2)
if chec
sa_ex8_2.m
%Maximum SIR beamforming
% example 8.2
d=.5;
N=3;
sig2=.001; % noise variance
theta=-pi/2:.01:pi/2;
ang=theta*180/pi;
th0=pi/6; % receive angle
th1=-pi/6; % first interfer
sa_ex8_13.m
%%%%%%%%%%%%%%%%%%%
%% Conjugate Gradient %%
%%%%%%%%%%%%%%%%%%%
%----- Givens -----%
K=20; % total number of data samples
sig2=.001;
d = .5; % element spacing in terms of wavelength d = l
sa_fig3_16.m
% Smart Antennas figure 3.16 calculate the polar patterns for the finite length dipole and the 3-D patterns
% Lolam= L/lambda;
th=-pi:.01:pi;
lolam=.5:.5:1.5;
u1=((cos(pi*lolam(1)*cos(th))-cos(pi*
sa_fig3_17.m
% Smart Antennas Figure 3.17 plotting the directivity vs. finite dipole length in wavelengths
F=inline('((cos(pi*ll*cos(x))-cos(pi*ll))./sin(x)).^2.*sin(x)')
delta=.01;
x=delta:delta:pi;
for i
sa_fig3_7.m
% Smart antennas figure 3.7. 3-D pattern for cos(theta)^4 pattern
% use 100 data points in theta and 100 data points in phi
tend=pi/2;
set(0,'defaultfigurecolor','w')
fx=inline('abs(sin(3*pi*sin
sa_ex8_1.m
%Godara Method
% Example 8.1
d=.5;
N=5;
sig2=.001
theta=-pi/2:.01:pi/2;
ang=theta*180/pi;
th0=0; % receive angle
th1=-15*pi/180; % first interferer angle
th2=25*pi/180;
sa_fig6_25.m
% Angular distribution for a circle of scatterers
thmax=pi/4;
th=-pi/4:pi/400:pi/4;
f=2*sqrt(thmax^2-th.^2)/thmax^2;
figure;
plot(th*180/pi,f,'k')
xlabel('Arrival Angle')
Ylabel('PAP')
axis(
sa_fig4_24.m
% Smart Antennas figure4.24 plotting elevation plane pattern
a=1;
N=10;
pinc=2*pi/N;
th=-pi/2:.01:pi/2;
th0=pi/6;
ph0=0;
AF=zeros(1,length(th));
for n=1:N
AF=AF+exp(-1j*2*pi*a*(sin(th
sa_fig6_22.m
% Angular distribution for a circle of scatterers
thmax=pi/4;
th=-pi/4+.01:.001:pi/4-.01;
f=1./sqrt(thmax^2-th.^2);
figure;
plot(th*180/pi,f,'k')
xlabel('Arrival Angle')
Ylabel('PAP')
axis([