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A randomised approach for NARX model identification based on a multivariate Bernoulli distribution
2016
International Journal of Systems Science
The identification of polynomial NARX models is typically performed by incremental model building techniques that progressively select from a candidate set the terms (regressors) to include in the model. The main limitation of these methods stems from the difficulty to correctly assess the importance of each regressor based on the evaluation of partial individual models, which may ultimately lead to erroneous model selections. A more robust assessment of the significance of a specific model
doi:10.1080/00207721.2016.1244309
fatcat:lxwsfnbwwvhkjfmzegmnv3vony