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Maximum entropy spectral analysis



Maximum entropy spectral analysis (MaxEnt spectral analysis) is a method of improving spectral quality based on the principle of maximum entropy. It is simply the application of maximum entropy modeling to any type of spectrum and is used in all fields where data is presented in spectral form. The usefulness of the technique varies based on the source of the spectral data since it is dependent on the amount of assumed knowledge about the spectrum that can be applied to the model.

In maximum entropy modeling probability distributions are created on the basis of that which is known, and leads to a type of statistical inference about the missing information which is called the maximum entropy estimate. For example in spectral analysis the expected peak shape is often known, but in a noisy spectrum the center of the peak may not be clear. In such a case inputting the known information allows the maximum entropy model to derive a better estimate of the center of the peak, thus improving spectral accuracy.

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This article is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article "Maximum_entropy_spectral_analysis". A list of authors is available in Wikipedia.
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