Difference between revisions of "Main Page"

From Latent Variable Methods in Engineering
Jump to navigation Jump to search
m
m
Line 22: Line 22:
* All course videos are at the link (see above this line)
* All course videos are at the link (see above this line)
* Please read [http://literature.connectmv.com/item/44/partial-least-squares-regression-a-tutorial this PLS tutorial] before the next class as a recap of PLS.
* Please read [http://literature.connectmv.com/item/44/partial-least-squares-regression-a-tutorial this PLS tutorial] before the next class as a recap of PLS.
* The next class continues with PLS and also looks at soft sensors. Read [http://literature.connectmv.com/item/17/development-of-inferential-process-models-using-pls this paper for background] before next class.
* The next class continues with PLS and also looks at soft sensors. Read [http://literature.connectmv.com/item/17/development-of-inferential-process-models-using-pls this paper] and [http://www.isa.org/InTechTemplate.cfm?Section=Archives4&template=/ContentManagement/ContentDisplay.cfm&ContentID=18045 this trade publication] for background before next class.
* Please note that from this Friday onwards, I will start classes at 15:00 (except for 1 class that starts at 16:00).
* Please note that from this Friday onwards, I will start classes at 15:00 (except for 1 class that starts at 16:00).


Revision as of 00:31, 18 October 2011

Latent Variable Methods for Engineering: CHE 765


Administrative
Crystal Clear action configure.png

Announcements

  • All course videos are at the link (see above this line)
  • Please read this PLS tutorial before the next class as a recap of PLS.
  • The next class continues with PLS and also looks at soft sensors. Read this paper and this trade publication for background before next class.
  • Please note that from this Friday onwards, I will start classes at 15:00 (except for 1 class that starts at 16:00).
Class materials
Crystal Clear app korganizer.png

1: Course overview and introduction to latent variable methods

2,3,4: Principal component analysis (PCA)

4,5: Application of PCA to process monitoring

6: Projection to latent structures (PLS)

7,8,9 Applications of latent variable methods

10 Dealing with 3D data: batch and image data

11 Multiblock data analysis: dealing with data from multiple sources

12 Optimization and new product development

13 Course project presentations

Assignments, projects and datasets
Crystal Clear app kedit.png

Assignments

Project

  • Course project description

Crystal Clear mimetype spreadsheet.png All course datasets


Course calendar

Retrieved from "https://learnche.org/wiki_latent/index.php?title=Main_Page&oldid=81"