Thanks! I've not yet dived deep into kalman filters but only done hhm a bit and therefore hoped to get exactly this relationship uncovered.
Can you summarize or link to this relationship :) ?
Can you summarize or link to this relationship :) ?
In Kalman filters, you assume the unobserved state is Gaussian-ish and it moves continuously according to linear-ish dynamics (depending on which flavor of Kalman filter is being used).
In HMMs, you assume the hidden state is one of a few classes, and the movement among these states uses a discrete Markov chain.
In my experience, the algorithms are often pretty different for these two cases, but the underlying idea is very similar.