Filtering and Prediction for Discrete Systems with Unknown Input Using Nonparametric Algorithms

被引：0

作者：

Koshkin, Gennady M. ^{[1
]}

Smagin, Valery I. ^{[1
]}

机构：

[1] Tomsk State Univ, Dept Appl Math & Cybernet, Tomsk 634050, Russia

来源：

2014 10TH INTERNATIONAL CONFERENCE ON DIGITAL TECHNOLOGIES (DT) | 2014年

关键词：

Kalman filter; unknown input; filtering algorithm; prediction algorithm; nonparametric estimator; STATE ESTIMATION; LINEAR-SYSTEMS;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The paper addressed the filtering and prediction problems with using nonparametric algorithms for discrete stochastic systems with unknown input. The designed algorithms are based on combining the Kalman filter and nonparametric estimator. The optimal properties of the explored algorithms are proved. Examples are given to illustrate the usefulness of the proposed approach.

引用

页码：120 / 124

页数：5

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