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Introduction and Probability Review

  • Robert G. Gallager
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 321)

Abstract

A stochastic process (or random process) is a probabilistic experiment or model that evolves in time. That is, each sample point (i.e., possible outcome) of the experiment is a function of time called a sample function. The sample space is the set of possible sample functions, and the events are subsets of sample functions. Finally, there is a rule for determining the probabilities of the various events. As an example, we might be concerned with arrivals to some system. The arrivals might be incoming jobs for a computer system, arriving packets for a communication system, patients in a health care system, or orders for some merchandising warehouse.

Keywords

Sample Point Central Limit Theorem Sample Space Moment Generate Function Probability Mass Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Robert G. Gallager
    • 1
  1. 1.Massachusetts Institute of TechnologyUSA

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