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Interactions were inferred by means of mutual information calculations for a selected quantitative feature.
Outage probabilities, mutual information calculations and transmit diversity bounds for orthogonal amplify and forward (AF) and DF relaying are derived in[18] with the end-to-end performance being considered in[19] where DF is shown to perform better in terms of the ABER when compared to AF.
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To facilitate the mutual information calculation, we formalize the definition of mutual information as follows.
They quantify the information contained in the postsynaptic current amplitude about preceding inter-spike intervals using a mutual information calculation.
Using the sum of the ISIs in the mutual information calculation hides this dependence in the muscarine case, as anticipated.
We performed a mutual information calculation with a sum of the previous ISIs, successively adding more times.
Nevertheless, compared to FBCSP [14], this off-line analysis is indeed inexpensive in terms of computational cost in our method, neither involving mutual information calculation nor eigenvalue decomposition.
In an attempt to keep all the structure in a preceding inter-spike interval sequence we used a multivariate version of the mutual information calculation.
While all final results were from an ICU-wide analysis, the coupling information required in the mutual information calculation, i.e., the joint probability P xi,yj), was computed at the individual patient level.
This increase in variability is consistent with the statistically significant faster decorrelation time observed in the K = 1 mutual information calculation and in the increase in n-th order entropy and conditional entropy for n = 1.
After expression values are calculated, mutual information is calculated.
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