Neural Network Parameterizations of Electromagnetic Nucleon Form Factors

Understand

The electromagnetic nucleon form-factors data are studied with artificial feed forward neural networks.

• As a result the unbiased model-independent form-factor parametrizations are evaluated together with uncertainties.
• The Bayesian approach for the neural networks is adapted for chi2 error-like function and applied to the data analysis.
• The sequence of the feed forward neural networks with one hidden layer of units is considered.