Three Statistical Technologies with High Potential in Biological Imaging and Modeling

  • Moshe Fridman
  • J. Michael Steele
Part of the Basic Life Sciences book series (BLSC, volume 63)


The three technologies that are surveyed here are (1) wavelet approximations, (2) hidden Markov models, and (3) the Markov chain Renaissance. The intention of the article is to provide an introduction to the benefits these technologies offer and to explain as far as possible the sources of their effectiveness. We also hope to suggest some useful relationships between these technologies and issues of importance on the agenda of biological and medical research.


Markov Chain Simulated Annealing Hide Markov Model Gibbs Sampler State Sequence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Moshe Fridman
    • 1
  • J. Michael Steele
    • 1
  1. 1.Department of StatisticsUniversity of PennsylvaniaPhiladelphiaUSA

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