STOCHASTIC AND WORST-CASE SYSTEM-IDENTIFICATION ARE NOT NECESSARILY INCOMPATIBLE

被引：2

作者：

BAI, EW ^{[1
]}

ANDERSLAND, MS ^{[1
]}

机构：

[1] UNIV IOWA,DEPT ELECT & COMP ENGN,IOWA CITY,IA 52242

来源：

AUTOMATICA | 1994年 / 30卷 / 09期

基金：

美国国家科学基金会;

关键词：

SYSTEM IDENTIFICATION; PARAMETER ESTIMATION; LEAST SQUARES ESTIMATION; IDENTIFICATION; ESTIMATION;

D O I：

10.1016/0005-1098(94)90017-5

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Stochastic and worst case approaches to system identification are different and are usually treated separately. In this communique we investigate the effect that a projection operator has on the worst case behavior of estimates derived by stochastic identification algorithms. We show that under certain assumptions the projections of the stochastic estimates are convergent in the worst case setting. We illustrate this result by applying it to least squares and maximum likelihood algorithms.

引用

页码：1491 / 1493

页数：3