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where k is the index of kth mixture component.
The covariance of each mixture component is set to the identity matrix.
Each HMM mixture component models a group of data that share common attributes.
For Gaussian mixture models, the same procedure can be applied to each mixture component.
With N fertilisation, high dominance of one mixture component should be avoided to achieve good performance.
Each mixture component is specifically designed to extract the local principal orientations in the data.
A mixture design was used to choose the percentage of each mixture component.
For mixture-of-Gaussian (MOG) models, (55) is evaluated separately for each mixture component to obtain separate estimates, and all mixture component probabilities are finally added to obtain the feature likelihood for state via (56).
The EM algorithm treats the unknown stimulus mixture component which the neuron responds to as unobserved data, or latent variables.
In constrained MLLR (CMLLR) [22], the covariance matrix of the mixture component is also transformed as (2).
where mav is the vector, andmv is the vector that indicates the mixture component for each state at each time.
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