Hidden Markov gating for prediction of change points in switching dynamical systems.
Stefan Liehr, Klaus Richard Pawelzik, Jens Kohlmorgen, Steven Lemm, Klaus‐Robert Müller · 1999
. The prediction of switching dynamical systems requires an identication of each individual dynamics and an early detection of mode changes. Here we present a unied framework of a mixtures of experts architecture and a generalized hidden Markov model (HMM) with a state space dependent transition matrix. The specialization of the experts in the dynamical regimes and the adaptation of the switching probabilities is performed simultaneously during the training procedure. We show that our method allows for a fast on{line detection of mode changes in cases where the most recent input data together with the last dynamical mode contain sucient information to indicate a dynamical change. 1. Introduction Non{stationarity is a severe problem in classication and prediction of dynamical systems. A framework for dealing with non{stationarity is the mixtures of experts architecture, introduced by Jacobs et al. [3]. The mixtures of experts framework aims at separating the seemingly comp...