Probabilities, Random Variables, and Random Processes: Digital and Analog |
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Page 244
... stationary we write X , X2 , and o } and omit the t . Second - Order Stationary Random Process The random process x ( t ) is said to be strictly stationary of order two if all second - order statistics associated with the random ...
... stationary we write X , X2 , and o } and omit the t . Second - Order Stationary Random Process The random process x ( t ) is said to be strictly stationary of order two if all second - order statistics associated with the random ...
Page 245
... random variables . Strictly Stationary Random Process A random process is said to be strictly stationary if for any n random variables , X1 , X2 , ... , X ,, which sample the process at t1 , 2 , ... ,, 3 ... X2 . 9 ( 6.5 ) where X , X2 ...
... random variables . Strictly Stationary Random Process A random process is said to be strictly stationary if for any n random variables , X1 , X2 , ... , X ,, which sample the process at t1 , 2 , ... ,, 3 ... X2 . 9 ( 6.5 ) where X , X2 ...
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Digital and Analog Michael O'Flynn. INTEGRALS OF RANDOM PROCESSES AND EXPECTED VALUES OF INTEGRALS Two important ... stationary zero - mean random process is a sta- tionary random process . ( b ) A weighted integral of a stationary ...
Digital and Analog Michael O'Flynn. INTEGRALS OF RANDOM PROCESSES AND EXPECTED VALUES OF INTEGRALS Two important ... stationary zero - mean random process is a sta- tionary random process . ( b ) A weighted integral of a stationary ...
Contents
1 | 3 |
5 | 54 |
General Formulation and Solution of Problems | 69 |
Copyright | |
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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