کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
695689 890312 2013 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Consistent identification of Wiener systems: A machine learning viewpoint
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
Consistent identification of Wiener systems: A machine learning viewpoint
چکیده انگلیسی

Wiener system identification has been recently performed by adopting a Bayesian semiparametric approach. In this framework, the linear system entering the first block is given a finite-dimensional parametrization, while nonparametric Gaussian regression is used to estimate the static nonlinearity in the second block. In this paper, we study the asymptotic behavior of this estimator when the number of noisy output samples tends to infinity without assuming the correctness of the Bayesian prior models. For this purpose, we interpret Wiener identification under a machine learning perspective. This allows us to extend recent results on function estimation in reproducing kernel Hilbert spaces to derive a condition guaranteeing the statistical consistency of the identification procedure. We also discuss how the violation of such a condition can lead to useless estimates of the Wiener structure.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Automatica - Volume 49, Issue 9, September 2013, Pages 2704–2712
نویسندگان
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