Urgent need to know how to implement EM algorithms with MATLab

There is a corresponding ** on the Internet, you can check it yourself!

Introduction to EM algorithms and MATLAB demonstration** (1D and multi-dimensional Gaussian mixed model learning algorithms).

Web Links.

1.EM algorithm program:

2. em image segmentation：

3.Bayesian Image Segmentation

Didn't find a suitable program** :-

1.EM algorithm program:

2. em image segmentation：

3.Bayesian Image Segmentation

Didn't find a suitable program** :-

x=varname2';

length=size(x,2);

pi0=;p0=;

q0=;pi=zeros(1,length);

a=zeros(1,length);the product of mu and xi, b=zeros(1,length); the product of 1-mu and xi, p1=zeros(1,length);

p2=zeros(1,length);

mu=zeros(1,length);

for i=1:length %i starting from 1mu(i)=(pi0*(p0..)^x(i)))1-p0).

1-x(i)))/((pi0*(p0.^x(i)))1-p0).^1-x(i)))1-pi0)*(q0.

x(i)))1-q0).^1-x(i)))

a(i)=mu(i)*x(i);

b(i)=(1-mu(i))*x(i);

endpi=sum(mu)/length

p1=sum(a)/sum(mu)

p2=sum(b)/sum(1-mu)

Is it the EM algorithm in the Bayesian net of probability graphs?

There are ready-made functions in MATLAB.

obj = ,k)

x is the data and k is the number of clusters.

For other uses, see doc

How to implement EM algorithms with MATLAB, about a specific set of data.

Expectation maximization algorithm (MAXIMIZATION) is a kind of colossal key modulation algorithm for maximum likelihood estimation or maximum posterior probability estimation of probabilistic parameter models with hidden variables.