This code is to estimate the parameter of model of MIXTURE Gauss which is popular model used in pattern classification . JAVA 寫的估計(jì)復(fù)合高斯模型中的參數(shù)
標(biāo)簽： model parameter estimate MIXTURE
上傳時(shí)間： 2015-04-10
上傳用戶：kikye
GUI FOR GENERATING MULTIVARIATE RANDOM VARIABLES FROM MIXTURE的matlab實(shí)現(xiàn)
標(biāo)簽： MULTIVARIATE GENERATING VARIABLES MIXTURE
上傳時(shí)間： 2014-01-24
上傳用戶：lvzhr
EM algorithm based on constrained MIXTURE Gaussion model
標(biāo)簽： constrained algorithm Gaussion MIXTURE
上傳時(shí)間： 2015-11-26
上傳用戶：123啊
Fit a multivariate gaussian MIXTURE by a cross-entropy method. Cross-Entropy is a powerfull tool to achieve stochastic multi-extremum optimization.
標(biāo)簽： Cross-Entropy cross-entropy multivariate powerfull
上傳時(shí)間： 2014-12-20
上傳用戶：love_stanford
gaussian MIXTURE modelling in matlab
標(biāo)簽： modelling gaussian MIXTURE matlab
上傳時(shí)間： 2016-02-28
上傳用戶：weixiao99
Creates a Gaussian MIXTURE model with specified architecture.MIX = GMM(DIM, NCENTRES, COVARTYPE) takes the dimension of the space DIM, the number of centres in the MIXTURE model and the type of the MIXTURE model, and returns a data structure MIX.
標(biāo)簽： architecture COVARTYPE specified Gaussian
上傳時(shí)間： 2016-04-28
上傳用戶：dyctj
％ EM algorithm for k multidimensional Gaussian MIXTURE estimation ％ ％ Inputs: ％ X(n,d) - input data, n=number of observations, d=dimension of variable ％ k - maximum number of Gaussian components allowed ％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none) ％ maxiter - maximum number of iteration allowed ([] for none) ％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) ％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) ％ ％ Ouputs: ％ W(1,k) - estimated weights of GM ％ M(d,k) - estimated mean vectors of GM ％ V(d,d,k) - estimated covariance matrices of GM ％ L - log likelihood of estimates ％
標(biāo)簽： multidimensional estimation algorithm Gaussian
上傳時(shí)間： 2013-12-03
上傳用戶：我們的船長
Optimization with Parabolas MIXTURE Distributions 數(shù)學(xué)算法
標(biāo)簽： Distributions Optimization Parabolas MIXTURE
上傳時(shí)間： 2014-01-09
上傳用戶：wendy15
gmmTrain: Parameter training for gaussian MIXTURE model (GMM)
標(biāo)簽： Parameter gmmTrain gaussian training
上傳時(shí)間： 2014-01-16
上傳用戶：chenbhdt
Gaussian MIXTURE Algorithm
標(biāo)簽： Algorithm Gaussian MIXTURE
上傳時(shí)間： 2014-01-13
上傳用戶：thesk123
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