Multi-step-ahead Multivariate Predictors: a Comparative Analysis

被引：3

作者：

Cescon, Marzia ^{[1
]}

Johansson, Rolf ^{[1
]}

机构：

[1] Lund Univ, Dept Automat Control, SE-22100 Lund, Sweden

来源：

49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2010年

关键词：

SUBSPACE IDENTIFICATION;

D O I：

10.1109/CDC.2010.5717179

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The focus of this article is to undertake a comparative analysis of multi-step-ahead linear multivariate predictors. The approach considered for the estimation will be based on geometrically reliable linear algebra tools, resorting to subspace identification methods. A crucial issue is quantification of both bias error and variance affecting the estimate of the prediction for increasing values of the look ahead when only a small number of samples is available. No complete theory is available so far, nor sufficient numerical experience. Therefore, the analysis of this paper aims at shading some lights on the topic providing some insights and help to develop some intuitions.

引用

页码：2837 / 2842

页数：6

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