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Stochastic Systems, Markov Chain has finite # of states, recurrent and aperiodic, ergodic has limiting probability, fundamental matrix F = M⋅S absorbing probability, Markov Chain has one-step transition matrix, states can be absorbing, aperiodic is ergodic, one-step transition matrix <math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> <mtext> M = </mtext> <mmultiscripts> <mrow> <mfenced open="(" close=")"> <mtext> I - T </mtext> </mfenced> </mrow> <none/> <mtext> -1 </mtext> </mmultiscripts> </mrow> </math> fundamental matrix, states that communicate belong to same class, Markov Chain is a Stochastic System