(1)主函数main.m代码：clc;clear all;close all;%% 读取图像root='./data';img=read_train(root);%% 提取特征img_feature=feature_lattice(img);%% 构造标签class=10;numberpclass=500;ann_label=zeros(class,numberpclass*class);ann_data=img_feature;for i=1:classfor j=numberpclass*(i-1)+1:numberpclass*iann_label(i,j)=1;endend%% 选定训练集和测试集k=rand(1,numberpclass*class); [m,n]=sort(k); ntraindata=4500;ntestdata=500;train_data=ann_data(:,n(1:ntraindata));test_data=ann_data(:,n(ntraindata+1:numberpclass*class));train_label=ann_label(:,n(1:ntraindata));test_label=ann_label(:,n(ntraindata+1:numberpclass*class));%% BP神经网络创建，训练和测试net=network_train(train_data,train_label);predict_label=network_test(test_data,net);%% 正确率计算[u,v]=find(test_label==1);label=u';error=label-predict_label;accuracy=size(find(error==0),2)/size(label,2);fprintf('正确率: \n')disp(accuracy);