Papers and Books of interest:
Rabiner, L. R., A Tutorial on Hidden Markov Models and Selected
Applications in Speech Recognition, Proceedings of the IEEE,
vol. 77, no. 2, Feb. 1989, pgs 257 - 285. There is a lot of notation but
verbose explanations accompany.
Dodge, Charles and Jerse, Thomas A. Computer Music: Synthesis,
Composition, and Performance, 2nd ed., Shirmer Books: New York,
1997. pgs 361-368 are of particular interest - composing music with
markov chains.
Grimmett, G.R. and Stirzaker, D.R. Probability and Random
Processes, 2nd ed., Clarendon Press: Oxford, 1994. Chapter 6 is on
Markov chains, intended for advanced undergrads.
Isaac, Richard. The Pleasures of Probability, Springer: New
York, 1995. Chapter 16 is on Markov Chains, intended for undergrads.
Paulos, John Allen. A Mathematician Reads the Newspaper,
BasicBooks: New York, 1995. pgs. 72-73, 135-137 have explanations of how
conditional probability arises in the real world.
Stewart, Ian. The Magical Maze, Weidenfeld & Nicolson:London,
1997. Intended for general audience, pgs 87-98 have some interesting
thoughts on conditional probability.
Bookmarks for Markov Chains (Hidden and Normal)
Markov Models
Software
- Some software packages (mainly for specific applications) involving Hidden Markov Models
- Hidden Markov Model (HMM) White Paper
- A pitch for GeneMatcher, a software package that uses HMM structure to recognize genes
- HMMpro: a hidden Markov model (HMM) simulator
- Software intended to build statistical models of proteins and gene sequences.
- Myers' Hidden Markov Model software
- Software intended to be used for
Explanations and Exercises
-
- Hidden Markov Models
- A sketchy adaptation of other explanations of HMMs.
- Hidden Markov Models
- A very good explanation of HMMs, with explanation of their use in speech recognition
- Markov Model Exercise
- An exercise of a markov model of the progress of diabetes, with a simulation based on this structure.
- Lecture 7: hidden Markov models
- A bunch of slides from a lecture on HMMs, some good pictures, but difficult to decipher without the original lecture.
- Markov Chains
- Lecture notes on Markov Chains, some of which are difficult to read. Look at the examples.
Applications
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- Hidden Markov Models for Interactive Learning of Hand Gestures
- Audiovisual Sensory Integration Using Hidden Markov Models
- Using Markov Models and Hidden Markov Models to Find Repetitive Extragenic Palindromic Sequences in Escherichia coli
- Finding Genes in Human DNA with a Hidden Markov Model
- Hidden Markov Model: Concept
- Starner's work with American Sign Language and Hidden Markov Models
- schro97: Pattern Recognition of International Crises using Hidden Markov Models
- Hidden Markov model sequence analysis
- Are the Hidden Markov Models Promising in Protein Research ?
Papers
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- William M. Spears: Publications about Markov Chains
- Statistics of Hidden Markov Models