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 3
... called uncountable . A set is said to be empty if it has no elements . The empty set is given the symbol Ø and is often called the null set . A finite set is one that is either empty or has elements that can be counted , with the ...
... called uncountable . A set is said to be empty if it has no elements . The empty set is given the symbol Ø and is often called the null set . A finite set is one that is either empty or has elements that can be counted , with the ...
Page 181
... called a continuous random process . Figure 6.1-1 is an illustration of this class of process . Thermal noise generated by any realizable network is a practical example of a waveform that is modeled as a sample function of a continuous ...
... called a continuous random process . Figure 6.1-1 is an illustration of this class of process . Thermal noise generated by any realizable network is a practical example of a waveform that is modeled as a sample function of a continuous ...
Page 308
... called finite - dimensional if , for some positive integer N and nonnegative integer M , Y [ n ] is some function ... called the order or dimension of the system . Any other system is infinite - dimensional . The function forms an input ...
... called finite - dimensional if , for some positive integer N and nonnegative integer M , Y [ n ] is some function ... called the order or dimension of the system . Any other system is infinite - dimensional . The function forms an input ...
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 |
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