Nonparametric Algorithms of Identification and Prediction in the ARX-Models

Abstract

To identify an unknown function defining of a nonlinear ARX-process, we use kernel regression estimators. The principal parts of mean square errors for these estimators are found. The proposed algorithms are applied to the real data processing.