function [y] = activeFcn(w,b,x)
% 输出函数
y = w*x + b;
n = length(y);
for i =1:n
    y(i)=1.0/(1+exp(-y(i)));
end
y;
end

%更新公式的实现(反向传播算法)
o_update = (y-out_put).*out_put.*(1-out_put);
h_update = ((w')*o_update).*hid_put.*(1-hid_put);

outw_update = learnFactor*(o_update*(hid_put'));
outb_update = learnFactor*o_update;
hidw_update = learnFactor*(h_update*(x'));
hidb_update = learnFactor*h_update;

w = w + outw_update;
b = b+ outb_update;
w_h = w_h +hidw_update;
b_h =b_h +hidb_update;