Probabilities, Random Variables, and Random Processes: Digital and Analog |
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Page 192
... sampled values is 1.2 s , then the sampled values are either from adjacent interval lengths ( of size 1 ) called case A , or the second sampled value is from an interval which is 1 length further away again , called case B , as 1.2 s ...
... sampled values is 1.2 s , then the sampled values are either from adjacent interval lengths ( of size 1 ) called case A , or the second sampled value is from an interval which is 1 length further away again , called case B , as 1.2 s ...
Page 194
... sampled values are from the same interval both samples have = P = 1- same value and the sampled values are P = P samples have different values = T The joint mass function utilizing conditional probability may be found and is shown in ...
... sampled values are from the same interval both samples have = P = 1- same value and the sampled values are P = P samples have different values = T The joint mass function utilizing conditional probability may be found and is shown in ...
Page 402
... sampled data . 2. The choice of a sampling rate to obtain the ... values and a specific recovery formula exists for doing this . This result ... values sampled every 7 = 1 / 2f , s . The recovery formula for any time t is ∞ x ( t ) = Σ x ...
... sampled data . 2. The choice of a sampling rate to obtain the ... values and a specific recovery formula exists for doing this . This result ... values sampled every 7 = 1 / 2f , s . The recovery formula for any time t is ∞ x ( t ) = Σ x ...
Contents
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5 | 54 |
General Formulation and Solution of Problems | 69 |
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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