The complete model

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Okay, so we've now got our generative hidden Markov model inside the States for the Galaxy ins.
There's a galaxy.
And there there's another galaxy in You're the calcium final state machine says First go here, take this calcium, generate some frames so randomly suppressed the bottom randomly sample from the calcium.
The finite state machines then says randomly, at each time step.
Either stay in the same state or go to the next state on becoming some probabilities on those things that will come onto later on DH.
Then we want next eight on the next date.
Okay, so there's a hidden Markov model.
Let's just wrap up in the last couple of minutes, it's mark off.
So the Markoff was a statistician, I guess.
But his name has become associated with a particular property of the model.
Is memory loss, in other words, assumes we move, make a transition and move on to the next frame.
We completely forget what we did in the past, so the probability of things in this frame is independent of things in the past that lets us use this equation.
We've got a very simple model of duration in the model that's this thing here, you much in the probability of going around here is nearly one.
The probability of moving on is one minus that it's highly likely will stay in the state for a really long time.
We had a very biassed coin that when we tossed the coin 999 times out of 1000 we got heads.
We'll go around here many, many, many times before moving on, and then we have a long duration here.
The probability on this transition gives us a duration model on the duration.
What is this place? Simple exponential decay model.