Probabilities, Random Variables, and Random Processes: Digital and Analog |
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Page 31
... Problem 1 . ( c ) Express the event the series lasts at least four games as the union of points in Problem 1 . 3. Can you intuitively assign a probability measure to the sample space of Problem 1 assuming that the teams have equal ...
... Problem 1 . ( c ) Express the event the series lasts at least four games as the union of points in Problem 1 . 3. Can you intuitively assign a probability measure to the sample space of Problem 1 assuming that the teams have equal ...
Page 66
... PROBLEMS Note : These problems are somewhat simple and fundamental . Since Chapter 3 is devoted to problem solving , it contains more challenging exercises . 1. Use the fundamental definition of NA P ( A ) = lim N → ∞ N to find the ...
... PROBLEMS Note : These problems are somewhat simple and fundamental . Since Chapter 3 is devoted to problem solving , it contains more challenging exercises . 1. Use the fundamental definition of NA P ( A ) = lim N → ∞ N to find the ...
Page 92
... Problem 2 . Is your solution to this problem unique ? List some operations that will not affect your solution , such as " reflecting y ( t ) , ” “ time shifting , " " time scaling , " and so on . 4. In an Irish village , 70 % of the men ...
... Problem 2 . Is your solution to this problem unique ? List some operations that will not affect your solution , such as " reflecting y ( t ) , ” “ time shifting , " " time scaling , " and so on . 4. In an Irish village , 70 % of the men ...
Contents
1 | 3 |
5 | 54 |
General Formulation and Solution of Problems | 69 |
Copyright | |
12 other sections not shown
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