w1?=?[-0.4???0.58???0.089;
????-0.31??0.27??-0.04;
????-0.38??0.055?-0.035;
????-0.15??0.53???0.011;
????-0.35??0.47???0.034;
?????0.17??0.69???0.1;
????-0.011?0.55??-0.18;
????-0.27??0.61???0.12;
????-0.065?0.49???0.0012;
????-0.12??0.054?-0.063];
w2?=?[?0.83???1.6??-0.014;
?????1.1????1.6???0.48;
????-0.44??-0.41??0.32;
?????0.047?-0.45??1.4;
?????0.28???0.35??3.1;
????-0.39??-0.48??0.11;
?????0.34??-0.079?0.14;
????-0.3???-0.22??2.2;
?????1.1????1.2??-0.46;
?????0.18??-0.11?-0.49];
xx1?=?[-0.7????0.58??0.089];
xx2?=?[0.047??-0.4???1.04];
?%求w1?w2均值m1?m2和總類內(nèi)離散度ws
?m1?=?mean（w1）‘;
?m2?=?mean（w2）‘;
?n1?=?size（w11）;
?n2?=?size（w21）;
?s1?=?cov（w1）*（n1-1）;??%類內(nèi)離散度矩陣就是類型方差矩陣，但是這里要注意一點(diǎn)：
?s2?=?cov（w2）*（n2-1）;??%matlab中算的協(xié)方差被縮小了n-1倍，所以要乘（n-1）
?sw?=?s1?+?s2;???????
?w??=?inv（sw）*（m1-m2）;?
?ym1?=?mean（w‘*m1）;?????%一維Y空間內(nèi)，各類樣品均值
?ym2?