Probabilities, Random Variables, and Random Processes: Digital and Analog |
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Page 28
... shown in Figure 1.9 or the points of Example 1.12 shown in Figure 1.10 could be used as the space governing the problem . The choice of which space to use would depend on the interest in the experiment . If the interest was only in the ...
... shown in Figure 1.9 or the points of Example 1.12 shown in Figure 1.10 could be used as the space governing the problem . The choice of which space to use would depend on the interest in the experiment . If the interest was only in the ...
Page 80
... shown plotted in Figure 3.2c . The function i ( t ) may be written as x ( t + ) or ∞ Σ g ( t − 2n + p ) -∞ and this is the periodic function x ( t ) shifted units to the left , as shown plotted in Figure 3.2d . Using the definition i ...
... shown plotted in Figure 3.2c . The function i ( t ) may be written as x ( t + ) or ∞ Σ g ( t − 2n + p ) -∞ and this is the periodic function x ( t ) shifted units to the left , as shown plotted in Figure 3.2d . Using the definition i ...
Page 194
... shown in Figure 5.7d . The correlation using Figure 5.7d is show - .. Rxe = K0 = 1X1 × √ ( 1 − T ) = ( 1-7 ) For the range : 1 < t < 2 , Using the same thought process as involved in part ( a ) , we can P Ple samples are from adjacent ...
... shown in Figure 5.7d . The correlation using Figure 5.7d is show - .. Rxe = K0 = 1X1 × √ ( 1 − T ) = ( 1-7 ) For the range : 1 < t < 2 , Using the same thought process as involved in part ( a ) , we can P Ple samples are from adjacent ...
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5 | 54 |
General Formulation and Solution of Problems | 69 |
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Common terms and phrases
A₁ autocorrelation function average axiom B₁ balls Chapter convolution correlation integrals cross-correlation cross-correlation function cumulative distribution function dadß defined definition delta function denoted derivation deterministic discrete Fourier transform discrete probability theory discrete random process DRILL SET ensemble ergodic evaluate event space Example finite first-order stationary formula fundamental theorem fxy(a fy(B fz(y given impulse response joint density function joint mass function Laplace transform linear system M₁ member waveform notation obtained otherwise output periodic function periodic waveform permutations plotted in Figure points power spectral density probability measure probability theory problem properties pulse px(a random input random phenomenon range Rxx(T sample description space sampled values second-order stationary set theory shown in Figure shown plotted signal sketch SOLUTION solved statistics Sxx(w Ticket Pays two-sided Laplace transform two-sided z transform typical member X₁ z transform zero-mean