How to implement PCA to differentiate the signals from each other.

3 ビュー (過去 30 日間)
karthikeyan chandrasekar
karthikeyan chandrasekar 2019 年 1 月 17 日
回答済み: John Navarro 2021 年 2 月 2 日
Hi i have 88345x4 data set of fault and healthy gearbox, now how do i apply PCA for this data set and how can i differentiate them using PCA analysis using matlab

回答 (1 件)

John Navarro
John Navarro 2021 年 2 月 2 日
By PCA did you mean Principal component analysis?
If so, PCA does not extract features, it evaluates their correlation and indicates the more useful ones. PCA is employed for feature selection, no feature extraction. It should be done according the expertise, the case of study, and the features of interest.
PCA will indicate which features would be more useful as classification criteria.
I recommend you to check documentation of other toolboxes related to classification and feature extraction (machine learning and statitics toolbox) and PM toolbox, instead of only information regarding signal processing toolbox.

カテゴリ

Help Center および File ExchangeDimensionality Reduction and Feature Extraction についてさらに検索

タグ

製品


リリース

R2018a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by