November 2012
Intermediate to advanced
794 pages
22h 9m
English
book
Probability, Random Variables, and Random Processes: Theory and Signal Processing Applications
by John J. Shynk
Content preview from Probability, Random Variables, and Random Processes: Theory and Signal Processing Applications
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SUMMARY OF NOTATION
| X | uppercase letter: random variable |
| X | lowercase letter: outcome of random variable X |
| |X| | absolute value of random variable X |
| X(n) | nth-order statistic |
|
estimator of X |
|
error random variable  |
| X | bold uppercase letter: random vector |
| X | bold lowercase letter: outcome of random vector X |
| X[k] | uppercase function of k: random sequence |
| X[k] | lowercase function of k: realization of X[k] |
| X(t) | uppercase function of t: random process |
| X(t) | lowercase function of t: realization of X(t) |
|
derivative random process |
| X[k] | bold uppercase function of k: random vector sequence |
| X[k] | bold lowercase function of k: realization of X[k] |
| X(t) | bold uppercase function of t: random vector process |
| X(t) | bold lowercase function of t: realization of X(t) |
|
convolution (continuous, discrete) |
|
deterministic cross-correlation (continuous, discrete) |
| X(s) | Laplace transform ... |
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.