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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Results 1-3 of 67
Page 340
... power spectrum and the aver- age power in the output signal . ( b ) Find the power spectrum of , and average power in , the output noise . ( c ) What is the ratio of the output signal's power to the output average noise power ? 8.4-14 . A ...
... power spectrum and the aver- age power in the output signal . ( b ) Find the power spectrum of , and average power in , the output noise . ( c ) What is the ratio of the output signal's power to the output average noise power ? 8.4-14 . A ...
Page 357
... noise power . This last criterion leads us to an optimum system often called a matched filter . 357 CHAPTER 9 : Optimum Linear Systems 9.1 SYSTEMS THAT MAXIMIZE SIGNAL - TO - NOISE RATIO An important class of systems involves the ...
... noise power . This last criterion leads us to an optimum system often called a matched filter . 357 CHAPTER 9 : Optimum Linear Systems 9.1 SYSTEMS THAT MAXIMIZE SIGNAL - TO - NOISE RATIO An important class of systems involves the ...
Page 372
... noise of power density No / 2 and the sum is applied to the input of a matched filter . The output peak signal - to - noise power ratio is 14 . What is o / 2 ? ( Hint : Use the results of Problem 9.1-8 . ) -8 9.1-30 . White noise , for ...
... noise of power density No / 2 and the sum is applied to the input of a matched filter . The output peak signal - to - noise power ratio is 14 . What is o / 2 ? ( Hint : Use the results of Problem 9.1-8 . ) -8 9.1-30 . White noise , for ...
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