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Two State Markov Process

Ryan Roper -

This example provides a simple continous-time Markov Process (or chain) model with two states: State A and State B. The model randomly switches between the two different states. When the model is in State A, the conditional container 'StateA' is activated. When in State B, the conditional container 'StateB' is activated. The model tracks the time in each state with an Integrator element. Logic and functionality could be added to each container to represent a particular Markov process by representing each state for the process in the appropriate conditional container.

Experience Level:

Advanced

Download the Model File:

Tags:

  • markov
  • conditional
  • container
  • event delay
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