Identification of nonlinear systems with missing data by the EM algorithm

被引：0

作者：

Tanaka, M ^{[1
]}

Dai, JS ^{[1
]}

机构：

[1] Okayama Univ, Dept Informat Technol, Okayama 700, Japan

来源：

(SYSID'97): SYSTEM IDENTIFICATION, VOLS 1-3 | 1998年

关键词：

identification; nonlinear systems; missing data; EM algorithm; Gaussian mixture distribution; Neural Network;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, identification of the joint probability dentisity function (PDF) from missing data is considered. The model of PDF is Gaussian mixture. It is well known that the expectation-maximization (EM) algorithm is useful for the identification of Gaussian mixture. Here it is extended to the case of missing elements of the observations. It will be shown that, after identifying the PDF model, it is easy to estimate the missing elements as well as the system output variable.

引用

页码：645 / 650

页数：6

共 50 条

[1] EM algorithm-based identification of a class of nonlinear Wiener systems with missing output data
Xiong, Weili
Yang, Xianqiang
Ke, Liang
Xu, Baoguo
[J]. NONLINEAR DYNAMICS, 2015, 80 (1-2) : 329 - 339
[2] EM algorithm-based identification of a class of nonlinear Wiener systems with missing output data
Weili Xiong
Xianqiang Yang
Liang Ke
Baoguo Xu
[J]. Nonlinear Dynamics, 2015, 80 : 329 - 339
[3] Identification of switched nonlinear systems based on EM algorithm
Chai Xiujun
Wang Hongwei
Wang Lin
Xiao Zhengqing
[J]. PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 1337 - 1342
[4] A Novel EM Identification Method for Hammerstein Systems With Missing Output Data
Wang, Dongqing
Zhang, Shuo
Gan, Min
Qiu, Jianlong
[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (04) : 2500 - 2508
[5] EM algorithm in Gaussian copula with missing data
Ding, Wei
Song, Peter X. -K.
[J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2016, 101 : 1 - 11
[6] Identification of nonlinear parameter varying systems with missing output data
Deng, Jing
Huang, Biao
[J]. AICHE JOURNAL, 2012, 58 (11) : 3454 - 3467
[7] Adjusting the EM algorithm for design of experiments with missing data
Dodge, Y
[J]. ITI 2004: PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY INTERFACES, 2004, : 9 - 12
[8] THE EM ALGORITHM FOR GRAPHICAL ASSOCIATION MODELS WITH MISSING DATA
LAURITZEN, SL
[J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 1995, 19 (02) : 191 - 201
[9] Robust identification for nonlinear errors-in-variables systems using the EM algorithm
Guo, F.
Hariprasad, K.
Huang, B.
Ding, Y. S.
[J]. JOURNAL OF PROCESS CONTROL, 2017, 54 : 129 - 137
[10] Identification of nonlinear systems with missing data using stochastic neural network
Tanaka, M
[J]. PROCEEDINGS OF THE 35TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4, 1996, : 933 - 934

← 1 2 3 4 5 →