An algorithm for identifying the ergodic subchains and transient states of a stochastic matrix is presented. Applications in Markov renewal programming and in the construction of variable length codes are reviewed, and an updating procedure for dealing with certain sequences of stochastic matrices is discussed. Computation times are investigated experimentally and compared with those of another recently proposed method.
Scientific Applications: An algorithm for identifying the ergodic subchains and transient states of a stochastic matrix
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