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数学计算 runs Kalman-Bucy filter over observations matrix Z for 1-step prediction onto matrix X (X can = Z)
runs Kalman-Bucy filter over observations matrix Z
for 1-step prediction onto matrix X (X can = Z)
with model order p
V = initial covariance of observation sequence noise
returns model parameter estimation sequence A,
sequence of predicted outcomes y_pred
and error matrix Ey (reshaped) for y and Ea ...
生物技术 This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise
This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal ...
书籍 Probability and Random Processes
Many good textbooks exist on probability and random processes written at the under-
graduate level to the research level. However, there is no one handy and ready book
that explains most of the essential topics, such as random variables and most of their
frequently used discrete and continuous proba ...
matlab例程 ％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input da
％ 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)
％ ...