Sentence examples for mutual information terms from inspiring English sources

For the Gaussian MIMO relay channel with the optimal Gaussian inputs, the mutual information terms specifying the rates boil down to the well-known log-det expressions.

There are two mutual information terms associated with phase 3 in (5): I ( X 1 ( 3 ) ; Y R ( 3 ) | X 2 ( 3 ) ) in the first condition and I ( X 2 ( 3 ) ; Y R ( 3 ) | X 1 ( 3 ) ) in the third one.

In these two extreme cases, several terms in (12) can be simplified: ● When r=1: I X 2 ; Y d 2 | W = 0 I X 2, W ; Y d 2 = I X 2 ; Y d 2. ● When r=0: I X 2 ; Y d 2 | W = I X 2, Y d 2 I X 2, W ; Y d 2 = I X 2, Y d 2 + I W ; Y d 2 | X 2. The mutual information terms in (12) are determined by both channel signal-to-noise ratio (SNR) and the input alphabet.

Of course, the timeslots timeshare a time-interval, which gives a weight to each mutual information term [25, Section ].

Under the assumption that all these measurements are independent, the mutual information term in (12) are derived from the distribution of channel input and the AWGN channel assumption.

When the mutual information term in the cost function is substantially greater than the constraint term, both the healthy tissue and the tumor area will be stretched during registration, and this could result in tumor expansion.

Predictions by SDPpred were compared with the highest scoring positions predicted by FRpred [ 36, 57] which combines a mutual information term with a conservation score.

To evaluate the mutual information term in equation (2), a b-spline estimator based on the work of [ 24] and implemented by Boris Hayete of the Gardner Lab as part of the CLR algorithm has been used.

We may now proceed by expressing the mutual information in terms of differential entropies provided the latter exists [30].

The predictions of the four methods are not significantly correlated to one another in terms of mutual information, although their overlap in terms of their positive predictions is low yet significant.

Given g i which represents the gene i, and the class label c, their mutual information is defined in terms of their frequencies of appearances p(g i ), p(c), and p(g i, c) as follows.