Nonlinear Model Order Selection: A GMM Clustering Approach Based on a Genetic Version of EM Algorithm

Algorithm 1

Typical EM Algorithm.

(i)	Initialization. Choose the number of components c, maximum of iterations iter_max, tolerance and the initial value of
(ii)	Repeat
(iii)	while or
(iv)	for (E-step)
	Compute the posterior probability generated by each component
	end for
(v)	for (M-step)
	Mean vector:
	Covariance matrix:
	Mixing coefficient:
(vi)	end for
	, update parameters
(vii)	end while
(viii)	The cluster is divided according to and then the completed covariance matrix is obtained