Nonparametric Algorithms of Identification and Prediction in the ARX-Models

被引：2

作者：

Koshkin, Gennady M. ^{[1
]}

Lukov, Vadim Yu. ^{[1
]}

Piven, Iosif G. ^{[1
]}

机构：

[1] Tomsk State Univ, Dept Appl Math & Cybernet, Tomsk, Russia

来源：

2016 SECOND INTERNATIONAL SYMPOSIUM ON STOCHASTIC MODELS IN RELIABILITY ENGINEERING, LIFE SCIENCE AND OPERATIONS MANAGEMENT (SMRLO) | 2016年

关键词：

ARX-processes; kernel estimators; regression function; FUNCTIONALS; AUTOREGRESSION; DENSITY; SENSE;

D O I：

10.1109/SMRLO.2016.109

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：620 / 623

页数：4

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