Efficient recursive canonical variate analysis approach for monitoring time-varying processes-Reference-Cited by-同舟云学术

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Efficient recursive canonical variate analysis approach for monitoring time-varying processes

Published:2016-11-23 Issue:1 Volume:31 Page:e2858
ISSN:0886-9383
Container-title:Journal of Chemometrics
language:en
Short-container-title:Journal of Chemometrics

Author:

Shang Liangliang¹²,Liu Jianchang¹³,Zhang Yingwei¹³,Wang Guozhu¹³

Affiliation:

1. College of Information Science and Engineering; Northeastern University; Shenyang 110819 Liaoning PR China

2. School of Electrical Engineering; Nantong University; Nantong 226019 Jiangsu PR China

3. State Key Laboratory of Synthetical Automation for Process Industries; Northeastern University; Shenyang 110819 Liaoning PR China

Funder

National Natural Science Foundation of China

State Key Laboratory of Integrated Automation of Process Industry Technology

Research Center of National Metallurgical Automation Fundamental Research Funds

Publisher

Wiley

Subject

Applied Mathematics,Analytical Chemistry

Reference36 articles.

1. Adaptive monitoring of the process operation based on symbolic episode representation and hidden markov models with application toward an oil sand primary separation;Sammaknejad;Comput Chem Eng,2014

2. Fault detection using canonical variate analysis;Juricek;Ind Eng Chem Res,2004

3. Propagator-based methods for recursive subspace model identification;Mercère;Signal Process,2008

4. Recursive predictor-based subspace identification with application to the real-time closed-loop tracking of flutter;Houtzager;IEEE Trans Control Syst Technol,2012

5. An overview of subspace identification;Qin;Comput Chem Eng,2006

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