SDM（Supervised Descent Method）算法的简单实现

Supervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision代码实现，貌似有问题，求交流！

y=[1:3:28];
x=log(y);
N=size(y,2);
itercount=5;
c=mean(x);
tempx=ones(1,N);
tempx=tempx*c;
rs=zeros(1,itercount);
for it=1:itercount
sum1=0;
sum2=0;
for i=1:N
sum1=sum1+(exp(tempx(i))-y(i))*(x(i)-tempx(i));
sum2=sum2+(exp(tempx(i))-y(i))^2;
end
r=sum1/sum2;
rs(it)=r;
for i=1:N
tempx(i)=tempx(i)+rs(it)*(exp(tempx(i))-y(i));
end
% sum((tempx-x).*(tempx-x))
end
rs
y2=[1:1:60];
M=size(y2,2);
x2=ones(1,M);
x2=x2*c;
for it=1:itercount
for i=1:M
x2(i)=x2(i)+rs(it)*(exp(x2(i))-y2(i));
end
end
% x2
x3=log(y2);
plot(x2,y2);
hold on;
plot(x3,y2,'r.');