clear
%%%%%%%%%create simulation data%%%%%%%%%%
n=2;
N=40; %sample time for one calculation
L=10; %data for LS
M=4; %iterative number
total=L+M*N+n;
end_con=1*10^-7; %program end condition
sigma=0.1; %noise's variance square root
%four orders m sequence creator as input
z1=1;z2=1;z3=1;z4=0;
for i=1:total
if i~=1
z1=xor(x3,x4);
z2=x1;
z3=x2;
z4=x3;
end
z(i)=z4;
if z(i)>0.5
u(i)=-1;
else u(i)=1;
end
x1=z1;x2=z2;x3=z3;x4=z4;
end
figure(1);
stairs(u);
axis([0 total -1.5 1.5]);
%%%%%%%%%%get output%%%%%%%%%%%%%%
y(1)=0;y(2)=0;
epselon=sigma*randn(total,1); %noise
y(1)=1;y(2)=0.01;
for k=3:total
y(k)=1.5*y(k-1)-0.7*y(k-2)+u(k-1)+0.5*u(k-2)+epselon(k)-1.0*epsel
on(k-1)+0.2*epselon(k-2);
end
%%%%%%%%%step 1 initialization with Least square
method%%%%%%%%%%%%%%%%%%
for j=1:L-n
