Question

A two-state Markov chain is used to model a system that alternates between ON and OFF states (binary states). In every 20 ms interval the system decides whether to turn ON or OFF based on the digital signal received. The probability the system changes from OFF state to ON state and from ON state to OFF state are 0.00714 and 0.01 respectively. Assuming that the system is in the OFF state, derive and evaluate the time requires for all the n state probabilities at time n are within 1% of the limiting state probability vector by providing a step-by-step procedure.

          A two-state Markov chain is used to model a system that alternates between ON and OFF states (binary states). In every 20 ms interval the system decides whether to turn ON or OFF based on the digital signal received. The probability the system changes from OFF state to ON state and from ON state to OFF state are 0.00714 and 0.01 respectively. Assuming that the system is in the OFF state, derive and evaluate the time requires for all the n state probabilities at time n are within 1% of the limiting state probability vector by providing a step-by-step procedure.

A two-state Markov chain is used to model a system that alternates between ON and OFF states (binary states). In every 20 ms interval the system decides whether to turn ON or OFF based on the digital signal received. The probability the system changes from OFF state to ON state and from ON state to OFF state are 0.00714 and 0.01 respectively. Assuming that the system is in the OFF state, derive and evaluate the time requires for all the n state probabilities at time n are within 1% of the limiting state probability vector by providing a step-by-step procedure.

Added by Hugo M.

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