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Discrete Stochastic Processes

The objective of this course is to help the reader to understand the concepts of probability theory and how they apply to the rigorous construction of the most fundamental classes of stochastic processes. More broadly, its goal is to introduce analytical knowledge required for: network resource management, network dimensioning, network planning, evaluation and performance analysis and etc. 

 

  1. Introduction to probability
  2. Random Variables
  3. Poisson Process
  4. Discrete Time Markov Chains
  5. Continuous Time Markov Chains
  6. Introduction to Queuing Theory
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Graduate