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Exact(2)
Within-class covariance matrices were assumed to be equal, prior probabilities were not taken into account.
Bayesian learning of PMF was performed through MCMC algorithm where Gaussian-Wishart priors for Gaussian mean vectors and precision matrices were assumed.
Similar(58)
Similar results are found when the Gaussian matrices are assumed to be square and selfad-joint.
All matrices are assumed to be independent of the transversal coordinate.
In the sequel, if not explicitly stated, matrices are assumed to have compatible dimensions.
The uncertainties in the system matrices are assumed to be norm-bounded.
The two-channel matrices are assumed to be distributed with (mathcal {CN}(0,1)).
If not explicitly stated, matrices are assumed to have compatible dimensions.
If not explicitly stated the matrices are assumed to have compatible dimensions.
In our simulations, the elements of all the signaling channel matrices are assumed to be i.i.d.i.d
In this system, forward, skip and loop transitions between the states are allowed and the covariance matrices are assumed diagonal [6, 9, 10].
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