Iterative Optimization in Inverse Problems

6 Iterative Optimization in Inverse Problems

scribing a system that moves from one state into another, as time goes on.

In the hidden Markov model we are not able to observe the states directly;

they are hidden from us. Instead, we have indirect observations, such as

the colors of the marbles in our urns model.

The probability that the color numbered i will be drawn from the urn

numbered j is a

i,j

, with



I

i=1

a

,ij

= 1, for all j. The colors announced

are the visible states, while the unannounced urn numbers are the hidden

states.

There are several distinct objectives one can have, when using HMM.

We assume that the data is the list of colors, i.

• Evaluation: ...