Learning Hidden Markov Models Using Back-Propagation through Time
Hiroshi Mamitsuka · 1995
Hidden Markov models (HMMs for short) are a type of stochastic models that have been used for a number of applications including speech recognition. Recently, HMMs have been applied to biological sequences[1] as tools of sequence alignments, validating motif patterns and even predicting protein structures.