Maximum Entropy and Bayesian Methods

1. Front Matter

   Pages i-5

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2. Bayesian Inference and Maximum Entropy

   1. Front Matter

      Pages 7-7

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   2. Intersubjectivity, Relativistic Covariance, and Conditionals (A New Axiomatization)

      • O. Costa De Beauregard

      Pages 9-14

   3. Game Theoretical Equilibrium, Maximum Entropy and Minimum Information Discrimination

      • Flemming Topsøe

      Pages 15-23

   4. Entropy, Moments and Probability Theory

      • Sławomir Kopeć, G. Larry Bretthorst

      Pages 25-30

   5. Bayes-Optimal Visualization of Vector Fields

      • Robert W. Boesel, Yoram Bresler

      Pages 31-38

   6. A Survey of Convergence Results for Maximum Entropy Methods

      • J. M. Borwein, A. S. Lewis

      Pages 39-48

   7. Maximum Entropy Method and Digital Filter Design

      • Rabinder N. Madan

      Pages 49-54

   8. A Theoretical Performance Analysis of Bayesian and Information Theoretic Image Segmentation Criteria

      • Ian B. Kerfoot, Yoram Bresler

      Pages 55-61

   9. On Application of Maxent to Solving Fredholm Integral Equations

      • Sławomir Kopeć

      Pages 63-66

   10. An Algorithm to Process Signals Conveying Statistical Information

       • L. Rebollo Neira, A. Plastino

       Pages 67-72

   11. Generalization of the Maximum Entropy Concept and Certain ARMA Processes

       • S. Unnikrishna Pillai, Theodore I. Shim

       Pages 73-78

   12. Making Sense of Quantum Mechanics: Why You Should Believe in Hidden Variables

       • Anthony J. M. Garrett

       Pages 79-83

   13. Bayesian Methods and Court Decision-Making

       • G. A. Vignaux, Bernard Robertson

       Pages 85-92

   14. Wigmore Diagrams and Bayes Networks

       • G. A. Vignaux, Bernard Robertson

       Pages 93-98

   15. An Invariance Principle for Updating Probabilities

       • Vicente Solana

       Pages 99-112

   16. Alpha, Evidence, and the Entropic Prior

       • C. E. M. Strauss, D. H. Wolpert, D. R. Wolf

       Pages 113-120

   17. Uniformly Distributed Sequences and the Maximum Entropy Principle

       • D. Giuliani, J. L. Gruver

       Pages 121-125

   18. Duality Without Tears

       • Claude Lemaréchal

       Pages 127-132

3. Quantum Physics and Quantum Information

   1. Front Matter

      Pages 133-133

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The Twelfth International Workshop on Maximum Entropy and Bayesian Methods in Sciences and Engineering (MaxEnt 92) was held in Paris, France, at the Centre National de la Recherche Scientifique (CNRS), July 19-24, 1992. It is important to note that, since its creation in 1980 by some of the researchers of the physics department at the Wyoming University in Laramie, this was the second time that it took place in Europe, the first time was in 1988 in Cambridge. The two specificities of MaxEnt workshops are their spontaneous and informal charac­ ters which give the participants the possibility to discuss easily and to make very fruitful scientific and friendship relations among each others. This year's organizers had fixed two main objectives: i) to have more participants from the European countries, and ii) to give special interest to maximum entropy and Bayesian methods in signal and image processing. We are happy to see that we achieved these objectives: i) we had about 100 participants with more than 50 per cent from the European coun­ tries, ii) we received many papers in the signal and image processing subjects and we could dedicate a full day of the workshop to the image modelling, restoration and recon­ struction problems.

• entropy
• image restoration
• physics
• quantum information
• quantum physics
• quantum theory

• Groupe Problèmes Inverses, Laboratoire des Signaux et Systèmes (CNRS-ESE-UPS), Gif-sur-Yvette Cedex, France

  Ali Mohammad-Djafari, Guy Demoment

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