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Bayes Theorem and Maximum Entropy Principle in the Measurement Data Processing

Guangju Chen

Open publisher page 1 citations

Abstract

On the base of the Bayes theorem and Maximum entropy principle, the paper analyzes the measurement data characteristics and designs the inversion method of measurement data PDF by the combination of the Bayes theory and Maximum principle. The prior distribution and the likelihood function of measurement data PDF in the Bayes theorem are calculated using the Maximum entropy principle. The results are proved by the experiment of measuring frequency.

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What this paper is about

On the base of the Bayes theorem and Maximum entropy principle, the paper analyzes the measurement data characteristics and designs the inversion method of measurement data PDF by the combination of the Bayes theory and Maximum principle. The prior distribution and the likelihood function of measurement data PDF in the Bayes theorem are calculated using the Maximum entropy principle. The results are proved by the experiment of measuring frequency.

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Available abstract

On the base of the Bayes theorem and Maximum entropy principle, the paper analyzes the measurement data characteristics and designs the inversion method of measurement data PDF by the combination of the Bayes theory and Maximum principle. The prior distribution and the likelihood function of measurement data PDF in the Bayes theorem are calculated using the Maximum entropy principle. The results are proved by the experiment of measuring frequency.

Key concepts: Principle of maximum entropy, Bayes' theorem, Mathematics, Maximum entropy spectral estimation, Bayes error rate, Maximum entropy thermodynamics, Prior probability, Entropy (arrow of time)

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