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The covariance matrix encodes the mutual variance of several random variables.
Correlations between fructosamine and HbA1c are of the order of r = 0.8, meaning that 64% of the mutual variance is explained; however, the weakness in this methodology would tend to negate or underestimate the consistency of our findings.
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We had mutual respect, and mutual disagreement.
Besides the two exact solutions indicated above, we also present in Section 5 the means to obtain the mean and variance of mutual information using two approaches.
Using the mean and variance of the mutual information in (45) and (46), we obtain the approximations for the PDFs of the mutual information and outage probability, respectively.
Under this approach, we use the correlation function expression (19) to obtain the mean and variance of the mutual information.
We propose below two approaches to calculate the mean and variance of the mutual information (mathcal {I}_{A}).
Then, the feature points are clustered using a Bayesian framework, under the assumption that pairs of points belonging to a same person have a small variance in their mutual distance (quasi-rigid motion).
With this distribution of the LLRs, there is a one-to-one mapping between the mutual information Iext and the variance σ ext 2 given by I ext = J ( σ ext ), (24).
Under the assumption that LLRs generated by a CBV node are Gaussian with mean μ and variance 2μ, the mutual information I between the code bit represented by the CBV node and the LLR is given by I = J (12).
We discuss the dynamics of the mutual uncertainty, conditional uncertainty and conditional variance in terms of spin standard deviations.
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CEO of Professional Science Editing for Scientists @ prosciediting.com