function?[mu?sigma]?=?Bayesian_parameter_est（train_patterns?train_targets?sigma）
train_patterns=[35?53?55?46?72?76?49;
????46?67?65?63?67?80?56;
????49?57?60?50?70?75?60;
????44?55?57?59?76?78?54];
train_targets=[52?63?53?55?71?91?59;37?50?52?61?63?76?45];

%?Estimate?the?mean?using?the?Bayesian?parameter?estimation?for?Gaussian?mixture?algorithm估計平均值，用貝葉斯參數的估計作為簡縮高斯函數集算法
%?Inputs:
%?	patterns	-?Train?patterns
%	targets	-?Train?targets
%	sigma		-?The?covariance?matrix?for?each?class?每一類矩陣的協方差
%
%?Outputs
%	mu			-?The?estimated?mean?平均值
%	sigma		-?The?estimated?covariances?協方差

[NM]?=?size（train_patterns）;
Uclasses?=?unique（train_targets）;
Nuc?=?length（Uclasses）;

%Find?initial?estimates?for?mu?and?sigma?for?the?classes
mu0	=?zeros（Nuc?N）;
sigma0?=?zeros（Nuc?N?N）;
for?i?=?1:Nuc
????indices	=?find（train_targets?==?Uclasses（i））;
????mu0（i:）?=?mean（train_patterns（:indices）‘）;
????sigma0（i::）?