Beginning Statistical Signal Processing

The subject of *statistical signal processing*
requires a background
in probability theory, random variables, and stochastic processes
[201].
However, only a small subset of these topics is really necessary to
carry out practical spectrum analysis of noise-like signals
(Chapter 6) and to fit deterministic models to noisy data.
For a full textbook devoted to statistical signal processing, see,
*e.g.*, [121,95].
In this appendix, we will provide definitions for
some of the most commonly encountered terms.

- Stochastic Processes
- Probability Distribution
- Independent Events
- Random Variable
- Stochastic Process
- Stationary Stochastic Process
- Expected Value
- Mean
- Sample Mean
- Variance
- Sample Variance

- Correlation Analysis
- Cross-Correlation
- Cross-Power Spectral Density
- Autocorrelation
- Sample Autocorrelation
- Power Spectral Density
- Sample Power Spectral Density

- White Noise

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