Probabilities, Random Variables, and Random Processes: Digital and Analog |
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Page 25
... mutually exclusive , collectively exhaustive listing of all possible outcomes of the experiment . The term " finest grain " implies that each point or possible outcome represents a distinguishable outcome of the phenomenon within the ...
... mutually exclusive , collectively exhaustive listing of all possible outcomes of the experiment . The term " finest grain " implies that each point or possible outcome represents a distinguishable outcome of the phenomenon within the ...
Page 33
... mutually exclusive ? ( b ) If A and B are mutually exclusive , are A and B mutually exclusive ? ( c ) If A and B are mutually exclusive and collectively exhaustive , are A and B mutually exclusive and collectively exhaustive ? 5. The ...
... mutually exclusive ? ( b ) If A and B are mutually exclusive , are A and B mutually exclusive ? ( c ) If A and B are mutually exclusive and collectively exhaustive , are A and B mutually exclusive and collectively exhaustive ? 5. The ...
Page 67
... mutually exclusive points of the space . 5. Use the formulas for dependent and independent events ог P ( AA2 A3 A2 ) ... mutually exclusive events to evaluate the probabilities of the following events : ( a ) A team A wins a five - game ...
... mutually exclusive points of the space . 5. Use the formulas for dependent and independent events ог P ( AA2 A3 A2 ) ... mutually exclusive events to evaluate the probabilities of the following events : ( a ) A team A wins a five - game ...
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