function?Qa=Project_Pursuit（XaAlpha）
%%?輸入參數列表
%?X?本指標矩陣，n*p的矩陣，每一行為一個樣本
%?Xij表示第i行第j列指標，X是否已經均一化均可
%?a?投影向量，1*p的矩陣，元素取值范圍-1~1，要求其元素平方和等于1
%?Alpha?窗口半徑系數，典型取值0.1
X=[0.02?0.05?0.75?0.18;
???0.03?0.79?0.11?0.07;
???0.04?0.49?0.33?0.14;
???0.04?0.12?0.69?0.15;
???0.04?0.32?0.48?0.16;
???0.05?0.44?0.34?0.17;
???0.03?0.72?0.15?0.10;
???0.14?0.42?0.25?0.19;
???0.04?0.59?0.25?0.12;
???0.05?0.15?0.60?0.20;
???0.12?0.50?0.22?0.16;
???0.03?0.83?0.09?0.05;
???0.05?0.38?0.41?0.16;
???0.03?0.12?0.51?0.34;
???0.02?0.86?0.08?0.04;
???0.08?0.64?0.18?0.10;
???0.04?0.32?0.48?0.16;
???0.03?0.77?0.13?0.07;
???0.09?0.56?0.21?0.14];?
a=[a1a2a3a4a5a6a7a8a9a10a11a12a13a14a15a16a17a18a19];
Alpha=0.1;
%%?輸出參數列表
%?Qa?投影指標函數
%%?第0步：對a的預處理
b=sqrt（sum（a.^2））;
a=a/b;
%%?第一步：指標體系無量綱化???%?缺少負指標的歸一化處理
[np]=size（X）;
x=zeros（np）;
Xjmax=max（X）;
Xjmin=min（X）;
for?i=1:n
????x（i:）=（X（i:）-Xjmin）./（Xjmax-Xjmin）;
end
%%?第二步：構造投影指標函數
Z=zeros（n1）;
for?i=1:n
????Z（i）=sum（a.*x（i:））;
end
%%第三步：計算投影指標函數
%%?計算類間類內矩陣散度
meanZ=mean（Z）;
Sa=0;
for?k=1:n
????sa=（Z（i）-meanZ（i））.^2;
????Sa=Sa+sa;
????Sa=sqrt（Sa/n）;
end
R=Alpha*Sa;???%窗口半徑
Da=0;
for?k=1:n
????rik=abs（Z（i）-Z（k））;
????if?R>rik
????????Da=Da+rik;
????end
end
Qa=Sa*Da;

????

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2019-05-16?11:49??投影尋蹤法（matlab）\
?????文件???????43520??2019-05-12?19:08??投影尋蹤法（matlab）\matlab和投影尋蹤.doc
?????目錄???????????0??2019-05-16?11:49??投影尋蹤法（matlab）\PP-matlab\
?????文件?????????753??2010-04-20?15:22??投影尋蹤法（matlab）\PP-matlab\diaoyong.m
?????文件?????????118??2010-03-30?21:19??投影尋蹤法（matlab）\PP-matlab\Feasibility.m
?????文件????????3877??2010-03-30?21:50??投影尋蹤法（matlab）\PP-matlab\RAGA.m
?????文件?????????441??2010-03-30?21:19??投影尋蹤法（matlab）\PP-matlab\Target.m
?????文件????????1452??2019-05-12?19:16??投影尋蹤法（matlab）\Project_Pursuit.m
?????文件????????1155??2019-05-12?19:27??投影尋蹤法（matlab）\Untitled2.m