 The goal is to learn about formula_1 by observing formula_2.HMM stipulates that, for each time instance formula_6, the conditional probability distribution of formula_7 given the history formula_8 must NOT depend on formula_9.Hidden Markov models are known for their applications to reinforcement learning and temporal pattern recognition such as speech, handwriting, gesture recognition, part-of-speech tagging, musical score following, partial discharges and bioinformatics.