Probability, Random Variables, and Random Signal PrinciplesThere are now 134 examples and nearly 900 homework problems; and other topics expanded or added include discussion of probability as a relative frequency, permutations, combinations, transformations of random variables, ergodicity of random processes, laws of large numbers, estimation, various inequalities, properties of impulses, and chapter-end summaries. This new material will prove most useful for students concerned with modern digital systems."--BOOK JACKET. |
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Page xii
... Density * 6.7 Complex Random Processes 206 6.8 Summary Problems 7 Random Processes - Spectral Characteristic 7.0 Introduction 208 208 220 220 7.1 Power Density Spectrum and Its Properties 220 The Power Density Spectrum | Properties of ...
... Density * 6.7 Complex Random Processes 206 6.8 Summary Problems 7 Random Processes - Spectral Characteristic 7.0 Introduction 208 208 220 220 7.1 Power Density Spectrum and Its Properties 220 The Power Density Spectrum | Properties of ...
Page 225
Peyton Peebles. It says that the power density spectrum of the derivative X ( 1 ) = dX ( 1 ) / dt is w2 225 times the power spectrum of X ... Density Spectrum | Properties of the Power Density Spectrum Bandwidth of the Power Density Spectrum.
Peyton Peebles. It says that the power density spectrum of the derivative X ( 1 ) = dX ( 1 ) / dt is w2 225 times the power spectrum of X ... Density Spectrum | Properties of the Power Density Spectrum Bandwidth of the Power Density Spectrum.
Page 459
... density , 205-206 Poisson random variable , 55 , 100 , 102 , 175 Power : from autocorrelation function , 194 incremental available , 316 from power density spectrum , 223 in a random process , 194 , 221 194 in response of linear system ...
... density , 205-206 Poisson random variable , 55 , 100 , 102 , 175 Power : from autocorrelation function , 194 incremental available , 316 from power density spectrum , 223 in a random process , 194 , 221 194 in response of linear system ...
Contents
Venn Diagram Equality and Difference Union | 7 |
Joint Probability Conditional Probability Total | 18 |
The Random Variable | 107 |
Copyright | |
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Probability, Random Variables, and Random Signal Principles Peyton Z. Peebles No preview available - 2001 |
Common terms and phrases
amplitude applied assume autocorrelation function available power gain average power band-limited bandpass bandwidth CHAPTER characteristic function cos(wpt covariance cross-correlation cross-correlation function cross-power defined denoted discrete random variables discrete-time DT system ergodic event example expected value Fourier transform frequency fx(x fy(y gaussian random variables given impulse response independent random variables integral joint density function jointly wide-sense stationary k₁ Linear Systems lowpass mean value Multiple Random Variables noise figure noise power noise temperature Peebles power density spectrum power spectrum Problem properties random process random process X(t Random Signal Principles random variables X1 real constants resistor Rxy(t Ryy(t sample function sample space sequence signal x(t spectral stationary process statistically independent statistically independent random Systems with Random t₁ transfer function uncorrelated variance voltage W₁ W₂ waveform white noise wide-sense stationary X₁ xx(w Y₁ Y₂ zero zero-mean