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EM_GM
% 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
%( 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)
- 2008-04-27 15:51:27下载
- 积分:1
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autoregresion_model_of_voice
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- 2009-05-26 21:29:32下载
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Matlab
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- 2021-03-09 20:19:27下载
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rsl
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- 2011-06-05 11:59:13下载
- 积分:1
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adaptive subspace identification
自适应子空间辨识,通过输入输出数据,计算状态空间方程,建模并预测。(Adaptive subspace identification, through input and output data, calculates the state space equation, modeling and forecasting.)
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Codes_MandarKulkarni_DynamicTDDSelfbackhaul
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lec03
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calculate-lyapunov
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- 2013-10-06 16:32:22下载
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C4.5
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- 2011-12-23 21:08:30下载
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JIAQUAN32N
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