Consistency and asymptotic normality of some subspace algorithms for systems without observed inputs

被引：74

作者：

Bauer, D ^{[1
]}

Deistler, M ^{[1
]}

Scherrer, W ^{[1
]}

机构：

[1] Vienna Univ Technol, Inst Okonometrie Operat Res & Syst Theorie, A-1040 Vienna, Austria

来源：

AUTOMATICA | 1999年 / 35卷 / 07期

关键词：

subspace methods; identification; asymptotic analysis; discrete time systems; linear multivariable systems; state-space systems;

D O I：

10.1016/S0005-1098(99)00031-X

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Linear systems with unobserved white noise inputs are considered. A class of subspace estimates for the system matrices obtained by estimating the state in the first step is analyzed. The main result presented here states asymptotic normality of subspace estimates. In addition, a consistency result for the system matrix estimates is given. An algorithm to compute the asymptotic variances of the estimates is presented. In a final section the implications of the result are discussed. (C) 1999 Elsevier Science Ltd. All rights reserved.

引用

页码：1243 / 1254

页数：12

共 22 条

[1] MARKOVIAN REPRESENTATION OF STOCHASTIC-PROCESSES BY CANONICAL VARIABLES [J].