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Maximum Entropy Principles

  • Igor Grabec
  • Wolfgang Sachse
Part of the Springer Series in Synergetics book series (SSSYN, volume 68)

Abstract

The concept of information can be successfully utilized for the adaptation of a probability distribution to empirical data. In order to proceed to the formulation of the corresponding principle, let us first recall the expression for the empirical probability density for the case when all the samples are distinct
$$fe\left( x \right) = \frac{1}{N}\sum\limits_{i = 1}^N {\delta \left( {x - {x_i}} \right)} = \sum\limits_{i = 1}^N {{P_f}} \delta \left( {x - {x_i}} \right) $$
(1)

Keywords

Sample Point Sample Space Vector Quantization Reference Function Window Function 
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-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Igor Grabec
    • 1
  • Wolfgang Sachse
    • 2
  1. 1.Faculty of Mechanical EngineeringUniversity of LjubljanaLjubljanaSlovenia
  2. 2.Theoretical and Applied MechanicsCornell UniversityIthacaUSA

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