Implementation of Nonlinear Principal Component Analysis for Time series data for time series data application
13 views (last 30 days)
Show older comments
Good Day,
I would like be assisted with integrating a toolbox into Matlab software. The toolbox is called Nonlinear Principal Component Analysis(NLPCA). Here is a link to it:
http://www.nlpca.org/matlab.html. This toolbox implements a nonlinear version of linear Principal Component Analysis(PCA). PCA is radily available in Matlab, but i am interested in the Nonlinear version. This NLPCA is implemented by training a neural network in this toolbox. For my project, I want to implement this NLPCA on the timeseries data obtained from measuring instruments. I am not sure how to add this toolbox to My Matlab. I would appreciate the help I could get.
Secondly, I would like to be assisted with resources in relation to training a simple neural network on timeseries data. Even links would be appreciated. I learned that most people train neural networks on things like images. Not much on time series data.
0 Comments
Answers (1)
TC
on 3 Feb 2021
You can use this toolbox by simply downloading it and using it as a function in MATLAB.
Keep downloaded function in the directory (or path). and use [pc, net] = nlpca(Data, k) where Data is your dataset and k is the number of nonlinear components you want to extract. read its 'readme' file for more information.
0 Comments
See Also
Categories
Find more on Dimensionality Reduction and Feature Extraction in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!