L(2)-OVERBIASED, L(2)-UNDERBIASED AND L(2)-UNBIASED ESTIMATION OF TRANSFER-FUNCTIONS

被引：15

作者：

DEMOOR, B

GEVERS, M

GOODWIN, GC

机构：

[1] UNIV CATHOLIQUE LOUVAIN, CTR SYST ENGN & APPL MECH, B-1348 LOUVAIN, BELGIUM

[2] UNIV NEWCASTLE, DEPT ELECT ENGN & COMP SCI, CTR IND CONTROL SCI, NEWCASTLE, NSW 2308, AUSTRALIA

来源：

AUTOMATICA | 1994年 / 30卷 / 05期

关键词：

BIAS REDUCTION; CONSTRAINT THEORY; ESTIMATION THEORY; FREQUENCY RESPONSE; IDENTIFICATION; LEAST-SQUARES ESTIMATION; MODELING; MODEL REACTION; PARAMETER ESTIMATION;

D O I：

10.1016/0005-1098(94)90179-1

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 identification of an undermodeled transfer function from input-output data is stated as a constrained optimization problem. The constraints determine the identification procedure, the residual error and whether on average the magnitude of the frequency response is L2-overbiased, L2-underbiased or L2-unbiased, as measured by a certain weighted L2-bias integral. The L2-unbiased solutions are linear combinations of L2-overbiased and L2-underbiased solutions, which are precisely the classical least squares estimates. They can be obtained from the solution of certain eigenvalue problems.

引用

页码：893 / 898

页数：6