%%example75index
%==============
%==============

clc;
clear;
close;
%競爭神經網絡
Hcomp5=figure('color',[0.8 0.8 0.8],'position',[120 120 600 400],'name',...
   'example7.5','numbertitle','off');

%界面說明
uicontrol(Hcomp5,'style','text','units','normalized','position',[0.1 0.8 0.8 0.15],...
   'horizontal','center','string','例5．用主分量分析進行圖像壓縮','back',[0.8 0.8 0.8],...
   'fontsize',12,'fontWeight','bold');
%框架
uicontrol(Hcomp5,'style','frame','units','normalized','position',[0.1 0.1 0.45 0.7],...
   'back',[0.8 0.8 0.8]);

uicontrol(Hcomp5,'style','text','units','normalized','position',[0.12 0.47 0.42 0.3],...
   'string','輸入樣本是兩幅256色交通標志圖像，采用主分量分析，獲取其協方差矩陣的特征值及其對應的特征向量。通過分析特征值的方差貢獻率，對圖像進行特征提取從而實現圖像壓縮','back',[0.8 0.8 0.8],'horizontal','left','fontsize',12);


%按鈕
uicontrol(Hcomp5,'style','push','units','normalized','position',[0.57 0.7 0.18 0.1],...
   'string',' 實驗圖像','callback','example75_figure','fontsize',12);
uicontrol(Hcomp5,'style','push','units','normalized','position',[0.79 0.7 0.18 0.1],...
   'string','  特征值分布','callback','example75_eigenvalue','fontsize',12);
% uicontrol(Hcomp5,'style','push','units','normalized','position',[0.56 0.57 0.20 0.1],...
%    'string','3、訓 練 網 絡         ','callback','example75','fontsize',12);
uicontrol(Hcomp5,'style','push','units','normalized','position',[0.57 0.57 0.18 0.1],...
   'string','特征向量提取','callback','example75_eigenvector','fontsize',12);
uicontrol(Hcomp5,'style','push','units','normalized','position',[0.79 0.57 0.18 0.1],...
   'string','壓縮后的圖像','callback','example75_result','fontsize',12);


%查看函數
uicontrol(Hcomp5,'style','push','units','normalized','position',[0.78 0.25 0.20 0.1],...
   'string','查看網絡函數','callback','NNfunctionindex','fontsize',12);

%退出
uicontrol(Hcomp5,'style','push','units','normalized','position',[0.78 0.13 0.20 0.1],...
   'string','返       回','callback','close(Hcomp5);NNindex16','fontsize',12);
uicontrol(Hcomp5,'style','push','units','normalized','position',[0.78 0.01 0.20 0.1],...
   'string','退出系統','callback','close(Hcomp5)','fontsize',12);