August 2016
Intermediate to advanced
204 pages
3h 51m
English
A hidden Markov model (HMM) has invisible or unobservable states, but a visit to these hidden states results in the recording of observation that is a probabilistic function of the state. Given a sequence of observations, the problem is to infer the dynamical system that had produced the given sequence. This inference will result in a model for the underlying process. The three basic problems of HMMs are given below:
Scoring problem: The target is to find the probability of an observed sequence with HMM already given.
Alignment problem: Given a particular HMM, the target is to determine from an observation sequence the most likely sequence of underlying hidden states that might have generated ...