Abstract Hidden Markov chains are widely applied statistical models of stochastic processes, from fundamental physics and chemistry to finance, health, artificial intelligence. The hidden processes they generate notoriously complicated, however, even if the chain is finite state: no expression for their Shannon entropy rate exists, as set predictive features generically infinite. As such, date ...

We introduce the entropy rate of multidimensional cellular automata. This number is invariant under shift–commuting isomorphisms; as opposed to the entropy of such CA, it is always finite. The invariance property and the finiteness of the entropy rate result from basic results about the entropy of partitions of multidimensional cellular automata. We prove several results that show that entropy ...

Laser pulse heating of solid surface and entropy generation during the heating process are considered. Time exponentially decaying pulse is accommodated in the analysis and the laser pulse parameter (b1/b2) resulting in minimum entropy generation rate is computed. Analytical solutions for temperature rise are presented and volumetric entropy generation rate is formulated. Two laser pulses resul...

Estimation of the entropy rate of a stochastic process with unknown statistics, from a single sample path is a classical problem in information theory. While universal estimators for general families of processes exist, the estimates have not been accompanied by guarantees for fixed-length sample paths. We provide finite sample bounds on the convergence of a plug-in type estimator for the entro...

the aim of this study is to show that the measures derived from electrocardiogram (ecg) signals many a time perform better than the same measures obtained from heart rate (hr) signals. a comparison was made to investigate how far the nonlinear symbolic dynamics approach helps to characterize the nonlinear properties of ecg signals and hr signals, and thereby discriminate between normal and cong...