Ann K. Stehney
Moravian College

March 2002
 

Markov chains and hidden Markov models provide a framework for analyzing sequential data
such as natural language, digital speech, communications signals, and other time series.
We  will describe the ideas behind these models, algorithms for exploiting them, theoretical considerations,
and an array of applications.  Recalling Markov’s original 2-state analysis of Russian text,
our illustrations will be drawn from problems associated with written texts, including unsolved ciphers.