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Hence by the nonnegativity of relative entropy, 0 D(p Theorem 2.6.5 u) = log |X| H (X). (2.94)

cadre of leaders and held up as the structure of civil society. To this day rules, in one way or another, govern the spaces between us, and as we discussed earlier, serve us well in many areas. However, as we begin to consider in depth the new thinking needed to succeed in a world of HOW, we need to examine more deeply our relationship to rules, how our thinking about them helps us and, sometimes, holds us back.

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are not affected by the puncturing rule, as it is known that this can result in a reduction of the BER performance of the turbo code. The turbo code scheme is seen in Figure 7.15. The puncturing rule adopted in this example of a turbo code is such that the systematic output (1) (2) (2) c1 is always transmitted, together with one of the two outputs c1 or c2 that are alternately transmitted through the channel. In this case the puncturing matrices for each encoder of the

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The model chi-squared for this complete-interaction model (results not shown) is 500.177, with 25 degrees of freedom. The test for the interaction block is therefore (500.177 472.915) = 27.262. With 25 13 = 12 degrees of freedom, this is signi cant at p < .01. Individual crossproduct terms that are signi cant in the interaction model are the cross products of minority status with income to needs (as already discovered), communication style, and male nonassertiveness. An equivalent way to proceed for those who want to know only whether the model is different across groups is to test for group differences using an equivalent of the Chow test (Chow, 1960) in linear regression. As outlined by Allison (1999), the procedure is as follows. First, we estimate the model for the combined sample with minority status as one of the predictors (this allows the intercept to differ across groups, as is the case in the rst procedure). This is Model 2 in Table 20.2. Then we estimate the same model, minus the dummy for minority status, in each separate sample minority couples versus nonminority couples. The results are shown in Table 20.4, with Model 2 in Table 20.2 repeated as the rst column of the table (under the heading Combined Sample ) for comparison. The test for group differences is then 2 log L c [ 2 log L m + ( 2 log L nm )], where L c is the likelihood for the combined sample, L m is the likelihood for the minority sample, and L nm is the likelihood for the nonminority sample, all evaluated at the MLEs. Under the null hypothesis that model coef cients (excluding the intercept) are the same across groups, this statistic is distributed as

and the game has a value. In particular, a deviation from normal for either player worsens the mutual information from that player s standpoint. Can you discuss the implications of this Note: Part of the proof hinges on the entropy power inequality from Section 17.8, which states that if X and Y are independent random n-vectors with densities, then 2 n h(X+Y) 2 n h(X) + 2 n h(Y) .

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The application of bioelectrical impedance (electrical impedance in the medical eld)

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