A weighted total least squares estimator for multivariable systems with nearly maximum likelihood properties

被引：5
|
作者：
Guillaume, P [1 ]
Pintelon, R
Schoukens, J
机构：
[1] Free Univ Brussels, Dept Mech Engn, B-1050 Brussels, Belgium
[2] Free Univ Brussels, Elect Measurement Dept, B-1050 Brussels, Belgium
来源：
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | 1998年 / 47卷 / 04期
关键词：
errors-in-variables; (generalized) singular value decomposition; (generalized) total least squares; maximum likelihood; multivariable systems; parameter estimation; system identification;
D O I：
10.1109/19.744627
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The aim of the present paper is to develop a parametric estimator for linear time-invariant multivariable systems with nearly maximum likelihood properties. The estimator is based on the total least squares (TLS) method. It can be seen as an "optimally" weighted iterative generalized TLS (GTLS) estimator, combining the nice asymptotic properties of the maximum likelihood (ML) method with the global minimization property of the GTLS estimator.
引用
收藏
页码：818 / 822
页数：5
相关论文
共 50 条
  • [1] A weighted total least squares estimator for multivariable systems with nearly maximum likelihood properties
    Guillaume, P
    Pintelon, R
    Schoukens, J
    JOINT CONFERENCE - 1996: IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE & IMEKO TECHNICAL COMMITTEE 7, CONFERENCE PROCEEDINGS, VOLS I AND II: QUALITY MEASUREMENTS: THE INDISPENSABLE BRIDGE BETWEEN THEORY AND REALITY (NO MEASUREMENTS? NO SCIENCE!), 1996, : 282 - 287
  • [2] Maximum Likelihood Recursive Least Squares Estimation for Multivariable Systems
    Junhong Li
    Feng Ding
    Ping Jiang
    Daqi Zhu
    Circuits, Systems, and Signal Processing, 2014, 33 : 2971 - 2986
  • [3] Maximum Likelihood Recursive Least Squares Estimation for Multivariable Systems
    Li, Junhong
    Ding, Feng
    Jiang, Ping
    Zhu, Daqi
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2014, 33 (09) : 2971 - 2986
  • [4] Recursive Least-squares Estimation for Multivariable Systems Based on the Maximum Likelihood Principle
    Huafeng Xia
    Yongqing Yang
    Feng Ding
    International Journal of Control, Automation and Systems, 2020, 18 : 503 - 512
  • [5] Recursive Least-squares Estimation for Multivariable Systems Based on the Maximum Likelihood Principle
    Xia, Huafeng
    Yang, Yongqing
    Ding, Feng
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2020, 18 (02) : 503 - 512
  • [6] The Gaussian Maximum-Likelihood Estimator Versus the Optimally Weighted Least-Squares Estimator [Lecture Notes]
    Abdalmoaty, Mohamed Rasheed-Hilmy
    Hjalmarsson, Hakan
    Wahlberg, Bo
    IEEE SIGNAL PROCESSING MAGAZINE, 2020, 37 (06) : 195 - 199
  • [7] STRUCTURED TOTAL MAXIMUM LIKELIHOOD: AN ALTERNATIVE TO STRUCTURED TOTAL LEAST SQUARES
    Beck, Amir
    Eldar, Yonina C.
    SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 2010, 31 (05) : 2623 - 2649
  • [8] Maximum likelihood-based recursive least-squares estimation for multivariable systems using the data filtering technique
    Xia, Huafeng
    Yang, Yongqing
    Ding, Feng
    Alsaedi, Ahmed
    Hayat, Tasawar
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2019, 50 (06) : 1121 - 1135
  • [9] Convergence properties of the least squares estimation algorithm for multivariable systems
    Liu, Yanjun
    Ding, Feng
    APPLIED MATHEMATICAL MODELLING, 2013, 37 (1-2) : 476 - 483
  • [10] Maximum Likelihood-Based Recursive Least-Squares Algorithm for Multivariable Systems with Colored Noises Using the Decomposition Technique
    Huafeng Xia
    Yan Ji
    Ling Xu
    Tasawar Hayat
    Circuits, Systems, and Signal Processing, 2019, 38 : 986 - 1004
12345