Marco,
from the figures you have shown, with the white and red characters against a black background, I conclude that the algorithm really goes ahead by assigning each character in the text to one of the possible states.
When doing this, it tries to maximise the consistency of having each character always being generated by the same state, but also to alternate as much as possible.
In the end, the A and B matrices can be computed by simply doing the statistics on the state transitions and the mapping of characters to states.
What is not output, it seems, is the fraction of characters represented by each state, i.e. the ratio of red and white characters in these plots, but this can be computed from the components of the A matrix.
Not sure how this will come out. If we call the states 1 and 2 (I never figured out why the vast majority of software people prefer to start counting at 0...), and the A matrix looks like this:
Then:
p(state=1) = A(21) / { A(12) + A(21) }
and
p(state=2) = A(12) / { A(12) + A(21) }
FWIW....
from the figures you have shown, with the white and red characters against a black background, I conclude that the algorithm really goes ahead by assigning each character in the text to one of the possible states.
When doing this, it tries to maximise the consistency of having each character always being generated by the same state, but also to alternate as much as possible.
In the end, the A and B matrices can be computed by simply doing the statistics on the state transitions and the mapping of characters to states.
What is not output, it seems, is the fraction of characters represented by each state, i.e. the ratio of red and white characters in these plots, but this can be computed from the components of the A matrix.
Not sure how this will come out. If we call the states 1 and 2 (I never figured out why the vast majority of software people prefer to start counting at 0...), and the A matrix looks like this:
Quote: / \
| A(11) A(12) |
| |
| A(21) A(22) |
\ /
Then:
p(state=1) = A(21) / { A(12) + A(21) }
and
p(state=2) = A(12) / { A(12) + A(21) }
FWIW....