Chapter 10 Stochastic Processes

Yates & Goodman
Probability and Stochastic Process, 2nd ed.
Chapter 10 Stochastic Processes

http://en.wikipedia.org/wiki/Stochastic_process
One approach to stochastic processes treats them as functions of one or several deterministic arguments ("inputs", in most cases regarded as "time") whose values ("outputs") are random variables: non-deterministic (single) quantities which have certain probability distributions.

stochastic processes = random functions of time
-> time suquence of the events

time structure of a process vs. amplitude structure of a random variable
(autocorrelation function and autocovariance function vs. expected value and variance)

Poisson

Brownian

Gaussian

Wide sense stationary processes

cross-correlation

10.1 Definitions and Examples



NRZ 파형
http://en.wikipedia.org/wiki/Non-return-to-zero