Nonlinear and Non-Gaussian Dynamic Batch Process Monitoring Using a New Multiway Kernel Independent Component Analysis and Multidimensional Mutual Information Based Dissimilarity Approach-Reference-Cited by-同舟云学术

Nonlinear and Non-Gaussian Dynamic Batch Process Monitoring Using a New Multiway Kernel Independent Component Analysis and Multidimensional Mutual Information Based Dissimilarity Approach

Published:2012-08-09 Issue:33 Volume:51 Page:10910-10920
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Rashid Mudassir M.¹,Yu Jie¹

Affiliation:

1. Department of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada L8S 4L7

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ie301002h

Reference31 articles.

1. Analysis of operating data for evaluation, diagnosis and control of batch operations

2. Process monitoring of an industrial fed-batch fermentation

3. Industrial experiences with multivariate statistical analysis of batch process data

4. Variance component analysis based fault diagnosis of multi-layer overlay lithography processes

5. Multi-way principal components-and PLS-analysis

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