多项式_svm.m

通常情况下是线性的分类,但在复杂情况下,要把他转换到另一空间来,以便线性的分类, SVM有其优势,还能做非线性的波束形成.

close all;
clear all;
N=6;
M=8;
j=sqrt(-1);
len=100;
% rp.TNRdB=10;
% rp.INRdB=10;
% rp.mean_v  = 0; % mean of complex-valued AWGN
% rp.var_v   = 1; % variance of complex-valued AWGN
theta=[-20*pi/180,-10*pi/180,10*pi/180,20*pi/180,35*pi/180,50*pi/180];
s0=2*(rand(1,len)>0.5)-1;
s1=2*(rand(1,len)>0.5)-1;
s2=2*(rand(1,len)>0.5)-1;
s3=2*(rand(1,len)>0.5)-1;
s4=2*(rand(1,len)>0.5)-1;
s5=2*(rand(1,len)>0.5)-1;
% t=0:0.01:0.2;
% x=rectpuls(t,1);
% for i=1:len
%     x_bpsk1((i-1)*20+1:i*20)=s0(1,i)*x(1:20);%基带信号
%     x_bpsk2((i-1)*20+1:i*20)=s1(1,i)*x(1:20);
% end
s=[s0;s1;s2;s3;s4;s5];
for i=1:M
    for k=1:N
        A1(i,k)=exp(-j*pi*(i-1)*sin(theta(k)));%array responce
    end
end

X_nn=A1*s;
X=X_nn;
L=100;
a=zeros(1,L);
C=0.1;
y=s3;

for i=1:L
    sum=0;
   for k=1:L
       K=(X(:,i)'*X(:,k)+1).^2;
        sum=sum+a(k)*y(k)*K;
    end
    u=1/((X(:,i)'*X(:,i)+1).^2);
    a(i)=a(i)+u*(1-y(i)*sum);
    if a(i)<0
        a(i)=0;
    else if a(i)>C
            a(i)=C;
        end
    end
end

% w=zeros(M,1);
% i=1;
% for i=1:L
%    w=w+a(i)*y(i)*X_t(:,i);
% end

sita1=[-90:2:90];
sita=sita1*pi/180;
G_sita=zeros(1,length(sita));
a_sita_i=zeros(M,length(sita));
for i=1:length(sita)
     Gsita=0;
     a_sita_i(:,i)=[1;exp(-j*pi*sin(sita(i)));exp(-j*2*pi*sin(sita(i)));exp(-j*3*pi*sin(sita(i)));exp(-j*4*pi*sin(sita(i)));exp(-j*5*pi*sin(sita(i)));exp(-j*6*pi*sin(sita(i)));exp(-j*7*pi*sin(sita(i)))];
     for p=1:L
         K=(a_sita_i(:,i)'*X(:,p)+1).^2;
         Gsita= Gsita+a(p)*y(p)*K;
     end
     G_sita(i)=Gsita;
end


figure;
plot(sita1,10*log10(abs(G_sita)));
grid on ;