Structure and Randomness of Continuous-Time, Discrete-Event Processes
Author(s)Crutchfield, James P; Marzen, Sarah E.
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Loosely speaking, the Shannon entropy rate is used to gauge a stochastic process’ intrinsic randomness; the statistical complexity gives the cost of predicting the process. We calculate, for the first time, the entropy rate and statistical complexity of stochastic processes generated by finite unifilar hidden semi-Markov models—memoryful, state-dependent versions of renewal processes. Calculating these quantities requires introducing novel mathematical objects (ϵ-machines of hidden semi-Markov processes) and new information-theoretic methods to stochastic processes.
DepartmentMassachusetts Institute of Technology. Department of Physics
Journal of Statistical Physics
Marzen, Sarah E., and Crutchfield, James P. “Structure and Randomness of Continuous-Time, Discrete-Event Processes.” Journal of Statistical Physics 169, 2 (August 2017): 303–315 © 2017 Springer Science+Business Media, LLC
Author's final manuscript