A profile hidden Markov model (PHMM) is widely used in assigning protein sequences to protein families. In this model, the hidden states only depend on the previous hidden state and observations are independent given hidden states. In other words, in the PHMM, only the information of the left side of a hidden state is considered. However, it makes sense that considering the information of the b...

a profile hidden markov model (phmm) is widely used in assigning protein sequences to protein families. in this model, the hidden states only depend on the previous hidden state and observations are independent given hidden states. in other words, in the phmm, only the information of the left side of a hidden state is considered. however, it makes sense that considering the information of the b...

The Baum-Welch algorithm is a technique for the maximum likelihood parameter estimation of probabilistic functions of Markov processes. We apply this technique to nonstationary Markov processes and explore a relationship between the Baum-Welch algorithm and the BCJR algorithm. Furthermore, we apply the Baum-Welch algorithm to two nonstationary Markov processes and obtain the turbo decoding algo...