English

Equivalence of History and Generator Epsilon-Machines

Probability 2015-03-19 v2 Statistical Mechanics Information Theory math.IT Chaotic Dynamics Machine Learning

Abstract

Epsilon-machines are minimal, unifilar presentations of stationary stochastic processes. They were originally defined in the history machine sense, as hidden Markov models whose states are the equivalence classes of infinite pasts with the same probability distribution over futures. In analyzing synchronization, though, an alternative generator definition was given: unifilar, edge-emitting hidden Markov models with probabilistically distinct states. The key difference is that history epsilon-machines are defined by a process, whereas generator epsilon-machines define a process. We show here that these two definitions are equivalent in the finite-state case.

Keywords

Cite

@article{arxiv.1111.4500,
  title  = {Equivalence of History and Generator Epsilon-Machines},
  author = {Nicholas F. Travers and James P. Crutchfield},
  journal= {arXiv preprint arXiv:1111.4500},
  year   = {2015}
}

Comments

23 pages, 5 figures; http://csc.ucdavis.edu/~cmg/compmech/pubs/hgem.htm; Expanded literature review, additional examples and figures