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 78
... Expected Value of a Random Variable The everyday averaging procedure used in the above example carries over directly to random variables . In fact , if X is the discrete random variable " fractional dollar value of pocket coins , " it ...
... Expected Value of a Random Variable The everyday averaging procedure used in the above example carries over directly to random variables . In fact , if X is the discrete random variable " fractional dollar value of pocket coins , " it ...
Page 97
... Expectation PROBLEMS 3.1-1 . A discrete random variable X has possible values x ; = i , i = 1 , 2 , 3 , 4 , 5 , which occur with probabilities 0.4 , 0.25 , 0.15 , 0.1 , and 0.1 , respectively . Find the mean value X = E [ X ] of X. 3.1 ...
... Expectation PROBLEMS 3.1-1 . A discrete random variable X has possible values x ; = i , i = 1 , 2 , 3 , 4 , 5 , which occur with probabilities 0.4 , 0.25 , 0.15 , 0.1 , and 0.1 , respectively . Find the mean value X = E [ X ] of X. 3.1 ...
Page 141
... expectation is enlarged to include two or more random variables . Other operations invol- ving moments , characteristic functions , and transformations are all special applications of expectation . 5.1 EXPECTED VALUE OF A FUNCTION OF ...
... expectation is enlarged to include two or more random variables . Other operations invol- ving moments , characteristic functions , and transformations are all special applications of expectation . 5.1 EXPECTED VALUE OF A FUNCTION OF ...
Contents
Venn Diagram Equality and Difference Union | 7 |
Joint Probability Conditional Probability Total | 18 |
The Random Variable | 107 |
Copyright | |
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Other editions - View all
Probability, Random Variables, and Random Signal Principles Peyton Z. Peebles No preview available - 2001 |
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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