Algorithms, Dynamic Programming, Machine Learning, Artificial Intelligence, Markov Models.
denoted x, each of which produces an observation, denoted y. Next, there are parameters explaining how the HMM behaves over time: There are the Initial State Probabilities. For each possible state s[i], what is the probability of starting off at state s[i]? These probabilities are denoted π(s[i]).