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Table 2-3 Y X x1 x2 ( xm Totals S y1 f (x1, y1) f (x2, y1) ( f (xm, y1 ) f2 (y1 ) y2 f (x1, y2) f (x2, y2) ( f (xm, y2 ) f2 (y2 ) c c c c c yn f(x1, yn ) f(x2, yn ) ( f(xm, yn) f2 (yn) Totals T f1 (x1) f1 (x2) ( f1 (xm) 1 d Grand Total

Fig. 8-10

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For j 1, 2, . . . , m, these are indicated by the entry totals in the extreme right-hand column or margin of Table 2-3. Similarly the probability that Y yk is obtained by adding all entries in the column corresponding to yk and is given by

CHAP. 8]

f2(yk )

a f (xj, yk )

nonzero, the function is a damped cosine. Only negative values of are considered. If and ! are zero, the result is a constant. And nally, with ! 0 and nonzero, the result is an exponential decay function. In Table 8-1, several functions are given with corresponding values of s for the expression Aest .

There are 8 nodes, so n 8. There are 11 arcs, so e 11. The cyclomatic number is C 11 8 2 5:

(16)

Table 8-1 f t 10e 5 cos 500t 308 2e 3t cos 100t 458 100:0

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For k 1, 2, . . . , n, these are indicated by the entry totals in the bottom row or margin of Table 2-3. Because the probabilities (15) and (16) are obtained from the margins of the table, we often refer to f1(xj) and f2(yk) [or simply f1(x) and f2(y)] as the marginal probability functions of X and Y, respectively.

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A 10 5 2 100.0

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When Fig. 8-10 is examined for various values of s, the three cases are evident. If 0, there is no damping and the result is a cosine function with maximum values of Vm (not shown). If ! 0, the function is an exponential decay with an initial value Vm . And nally, with both ! and nonzero, the damped cosine is the result.

(17)

A planar graph is a graph that can be drawn without lines crossing. The Swiss mathematician Leonhard Euler (1707 1783) proved for planar graphs that

a a f (xj, yk)

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A driving voltage of the form v Vm est applied to a passive network will result in branch currents and voltages across the elements, each having the same time dependence est ; e.g., Ia e j est , and Vb e j est . Consequently, only the magnitudes of currents and voltages and the phase angles need be determined (this will also be the case in sinusoidal circuit analysis in 9). We are thus led to consider the network in the s-domain (see Fig. 8-11).

(18)

Fig. 8-11

This is simply the statement that the total probability of all entries is 1. The grand total of 1 is indicated in the lower right-hand corner of the table. The joint distribution function of X and Y is defined by F(x, y) P(X x, Y y) a a f (u, v) y. (19)

2. CONTINUOUS CASE. The case where both variables are continuous is obtained easily by analogy with the discrete case on replacing sums by integrals. Thus the joint probability function for the random variables X and Y (or, as it is more commonly called, the joint density function of X and Y ) is defined by 1. f(x, y)

A series RL circuit with an applied voltage v Vm e j est will result in a current i Im e j est Im est , which, substituted in the nodal equation Ri L will result in RIm est sLIm est Vm e j est from which Im Vm e j R sL The inductance theredi Vm e j est dt

2. 3

Note that in the s-domain the impedance of the series RL circuit is R sL. fore has an s-domain impedance sL.

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