Equivalence of linear boltzmann chains and hidden markov models

  • Authors:

  • David J. C. MacKay

  • Affiliations:

  • Cavendish Laboratory, Madingley Road, Cambridge CB3 0HE, United Kingdom

  • Venue:
  • Neural Computation
  • Year:
  • 1996

Quantified Score

Hi-index 0.01

Visualization

Abstract

Several authors have studied the relationship between hidden Markov models and “Boltzmann chains” with a linear or “time-sliced” architecture. Boltzmann chains model sequences of states by defining state-state transition energies instead of probabilities. In this note I demonstrate that under the simple condition that the state sequence has a mandatory end state, the probability distribution assigned by a strictly linear Boltzmann chain is identical to that assigned by a hidden Markov model.