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.
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© 1996 Springer Science+Business Media New York
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Gallager, R.G. (1996). Introduction and Probability Review. In: Discrete Stochastic Processes. The Springer International Series in Engineering and Computer Science, vol 321. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2329-1_1
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DOI: https://doi.org/10.1007/978-1-4615-2329-1_1
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5986-9
Online ISBN: 978-1-4615-2329-1
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