An Alternative Proof For the Minimum Fisher Information of Gaussian Distribution

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Abstract

Fisher information is of key importance in estimation theory. It is used as a tool for characterizing complex signals or systems, with applications, e.g. in biology, geophysics and signal processing. The problem of minimizing Fisher information in a set of distributions has been studied by many researchers. In this paper, based on some rather simple statistical reasoning, we provide an alternative proof for the fact that Gaussian distribution with finite variance minimizes the Fisher information over all distributions with the same variance.

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Journal of Applied Mathematics, Statistics and Informatics

The Journal of University of Saint Cyril and Metodius

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Mathematical Citation Quotient (MCQ) 2017: 0.06

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researchers in the fields of informatics, information technologies, statistics and mathematics

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