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Markov processes, the probabilities

Since both \boldsymbol{W} and \boldsymbol{w} represent probabilities, they have to be normalized, i.e., we require that at each time step we have

\begin{equation*} \sum_i w_i(t) = 1, \end{equation*}

and

\begin{equation*} \sum_j W(j\rightarrow i) = 1, \end{equation*}

which applies for all j -values. The further constraints are 0 \le W_{ij} \le 1 and 0 \le w_{j} \le 1 . Note that the probability for remaining at the same place is in general not necessarily equal zero.