Probabilities, Random Variables, and Random Processes: Digital and Analog |
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Page xi
... power spectral and cross - spectral densities , which define randomness through frequency . The chapter commences with a tutorial treatment of the transforms with which a modern student of system and communication theory is expected to ...
... power spectral and cross - spectral densities , which define randomness through frequency . The chapter commences with a tutorial treatment of the transforms with which a modern student of system and communication theory is expected to ...
Page 417
Digital and Analog Michael O'Flynn. We have already defined power spectral density S1 ( w ) to mean Pav = √ °° _Sxx ( w ) df 88 Therefore , observing Eq . 8.41 , we obtain a new ... POWER SPECTRAL DENSITY AND INPUT - OUTPUT RELATIONS 417.
Digital and Analog Michael O'Flynn. We have already defined power spectral density S1 ( w ) to mean Pav = √ °° _Sxx ( w ) df 88 Therefore , observing Eq . 8.41 , we obtain a new ... POWER SPECTRAL DENSITY AND INPUT - OUTPUT RELATIONS 417.
Page 432
... spectral densities that follow from the proper- ties of cross - correlation functions and Fourier transforms are ... power spectral density of a linear time - invariant causal system to its input power spectral density and the cross ...
... spectral densities that follow from the proper- ties of cross - correlation functions and Fourier transforms are ... power spectral density of a linear time - invariant causal system to its input power spectral density and the cross ...
Contents
1 | 3 |
5 | 54 |
General Formulation and Solution of Problems | 69 |
Copyright | |
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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