Their method, called "SOMN-HMM" (which stands for "self-organizing mixture networks" which are used to represent mixture of Gaussians in the HMMs), makes it possible to train basic HMMs as well as parametric HMMs containing a "style" parameter.
While it is possible that the HMM states inferred in this paper relate to the source space counterparts of EEG microstates, without measuring EEG and MEG concurrently, a direct relationship cannot be confirmed.
We have shortened our discussion of EEG microstates accordingly and have added the following: "While it is possible that the HMM states inferred in this paper relate to the source space counterparts of EEG microstates, without measuring EEG and MEG concurrently, a direct relationship cannot be confirmed".
Furthermore, it has not been possible to build an HMM that finds all PPP-nominated members of this family while systematically excluding all homologs from mycofactocin-negative genomes.
Notice that it is possible to derive a HMM using all 15 states, but the derivation of transition probabilities gets more involved.
The algorithm takes a HMM with possible Q states, initial probabilities π i where i is the current state of the model, and transition probabilities a i, j where i, j is the change from state i to state j.
In principle, however, whole-genome analysis is possible in the HDP-HMM framework.
These characteristics open up the possibility of applying the proposed message-passing scheme to accurate probabilistic alignment of genome-scale sequences, which has not been possible using traditional pair-HMMs.
I know we're all up to our necks in the spectacle of the Republican candidate debates and the last gasps of the super committee (hmm, is it possible some put kryptonite in their meeting room? Not sure that the Secret Service scans for that).
However, although it was obviously not possible to create a single HMM that detects all examples of this family the members are assumed to have arisen from a single evolutionary origin [24].
