chanl_adp_model_define.asv

lms算法的自己编的程序 包括各种影响因素的分析等等 包括运行结果分析图

format compact
format short g
clear;
clc;%close all
global n_total  var_noise  snr_tran  order_h 
%system paraments define
n_total=1024;% 总输入数据量
var_noise=1;  % the channel noise

snr=-10% dB forms at the transmitter=>var_signal=var_noise*10^(snr_tran/10)(transmit)
order_h=5;     %the order of the adptive filter's transmit vector

%paraments of the channel:channel noise
init=2788605800;  randn('seed',init);  clear init;
for m=1:2
noise=sqrt(var_noise)*randn(1,n_total); 

k=linspace(0,2*pi*10,n_total);
signal=sqrt( var_noise*10.^(snr/20) )*sqrt(2)*sin(k);


b00=xcorr(noise+signal);
b000=b00(n_total:2*n_total-1);
for i=1:50
    for j=1:50
        matrix_zixiangguan(i,j)=b00(abs(i-j)+1);
    end
end
lampt_max=max(abs(eig(matrix_zixiangguan)))
lampt_min=min(abs(eig(matrix_zixiangguan)))
u_max=2/lampt_max
kaifang(m)=abs(lampt_max/lampt_min)
snr=snr+1;
plot(snr,kaifang(m),'*')
hold on

end
clear b000 b00 matrix_zixiangguan