Hierarchical General Hidden Markov Model Plugin - Fixed Batch
The Hierarchical General Hidden Markov Model - Fixed Batch (HMM-Batch) plugin is
a generalized version of the GHMM one, and was implemented during the work of
[#!carolina2007!#]. Inside each state, instead of a simple Gilbert model, the
user can define a general Markov chain, which, as in the case of the GHMM, is
responsible for the symbol emissions. Figure
illustrates the
structure of such a hierarchical model.
Figure:
Example of a hierarchical general HMM with 2 hidden states and 4
observation symbols.
![\includegraphics[width=1.0\textwidth]{figuras/mtk_hmm_module/hmm_batch.eps}](img333.png) |
After each transition
in the the hidden chain (the upper-level
one), the lower-level model associated with
emits symbols by transiting
for a fixed number of steps, called a batch, before the upper-level chain
makes another transition11.10. Every time the lower-level Markov chain makes one
transition, thus reaching one of its states, the model emits one symbol, which
is the one associated with the lower-level state just reached. Hence, symbol
is emitted every time the lower-level state
is reached, where
,
with
, defines a lower-level state inside the hidden
state
. Each lower-level state emits one, and only one, symbol, and
different lower-level states, inside a same hidden state, cannot both emit the
same symbol.
Subsections
Guilherme Dutra Gonzaga Jaime
2010-10-27