How Random is a Coin Toss? Bayesian Inference and the Symbolic Dynamics of Deterministic Chaos

Posted in Science on September 07, 2008


How Random is a Coin Toss? Bayesian Inference and the Symbolic Dynamics of Deterministic Chaos

Lecture slides:

  • How Random is a Coin Toss?
  • Sources of Randomness
  • A model of measurement
  • Modeling chaotic time series
  • Our model data source
  • Rossler Attractor
  • Designing an instrument
  • Symbolic Dynamics
  • Choose a partition P
  • Testing the resulting partition
  • Bayes’ Theorem
  • Likelihood
  • Prior
  • Evidence
  • Posterior
  • Model comparison
  • Estimating hì
  • An experiment
  • Methods
  • Instrument design
  • Model Inference
  • Conclusion

Author: Christopher Strelioff, Center For Complex Systems Research And Department Of Physics, University Of Illinois At Urbana Champaign, University Of Illinois

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Tags: Science, Lectures, Computer Science, Machine Learning, VideoLectures.Net, Bayesian Learning