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Monitoring and treatment of multiple environmental parameters are mutually independent, with low instantaneity and reliability.
The subvectors are assumed to be mutually independent with variance θ i 2 I b i.
Classically it is assumed that the residuals ε i t are normally distributed and mutually independent with mean zero and constant variance, i.e., ε it ∼ iid N (0, σ ϵ 2 ).
It is assumed that the residuals ε i t are normally distributed and mutually independent with mean zero and constant variance, i.e., ε it ∼ iid N (0, σ ϵ 2 ).
In this way, the distributions of pseudo pathways are similar to their corresponding real pathways, and therefore, we assume that the null hypothesis could be regarded as that the diseases are mutually independent with each other, and the alternate hypothesis is that the diseases links are different from random links.
It is assumed that b0 i and ε i t are normally distributed and mutually independent with mean zero and different constant variances, i.e., b 0 i ∼ N (0, σ b 0 2 ), and ε it ∼ N (0, σ ϵ 2 ) [ 21].
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where is the input vector satisfying the total power constraint and, are mutually independent AWGN with covariance.
where is the transmit vector satisfying the total power constraint and, are mutually independent AWGN with covariance.
where are mutually independent Gaussian vectors with zero mean and covariance satisfying.
The phenomena of the randomly occurring uncertainties and packet dropouts are characterized by utilizing mutually independent random variables with known occurrence probabilities.
where the common message vector and the confidential message vector are mutually independent Gaussian vectors with zero mean and covariance,, respectively.
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