nn_5.m

以bp模擬碗公!!並加以訓練然後再佳以模擬內容簡單歡迎下載

clc
clear all
close all
rand('seed',12345);
epoch=100000;
learn=0.1;
alpha=0; 
delta_w1=0;
delta_w2=0;
bias1=ones(1,300);
bias2=ones(1,100);
neural_1=5;
neural_2=5;
% ===============================================================
[x1,x2]=meshgrid(linspace(-5,5,20));
yyy=x1.^2 + x2.^2;





input_x1=x1(:);
input_x2=x2(:);
all_input = [input_x1 input_x2];
 box1=randperm(400);
 box2=randperm(400);
xx1=input_x1(box1);
xx2=input_x2(box2);

training_patern = [xx1(1:300) xx2(1:300)];
test_pattern = [xx1(301:400) xx2(301:400)];
x_input1=[training_patern';bias1];
x_input2=[test_pattern';bias2];
%================================================================
 d=training_patern(:,1).^2+training_patern(:,2).^2;
 d1=test_pattern(:,1).^2+test_pattern(:,2).^2;
ynew=(d-(0))/(50-(0))*0.6+0.2;%normalize


%===========================================================倒﹚training_patern,test_pattern
 
 
weight1=0.3*rands(neural_1,3);
weight2=0.3*rands(neural_2,1);

wait=waitbar(0,[''],'name','叫祔