Principal Component Analysis (PCA) on images in MATLAB (GUI)
Feature level fusion using Canonical Correlation Analysis (CCA)
The function MVMD applies the Multivariate Variational Mode Decomposition (MVMD) algorithm to multivariate or multichannel data.
Feature fusion using Discriminant Correlation Analysis (DCA)
This function plots a workspace for a planar n-DOF revolute or prismatic given DH parameters and the constraints of all variables.
Arranging the following blocktype (inports, outports ,from-goto blocks , terminator) connected to Subsystem.
Get elevations from Google Maps (Google API key required) from latitute and longitude, coordinates input (UTM)
When analyzing very high-dimensional data, this implementation of Principal Component Analysis is much faster than MATLAB's pca.m.
Dynamic Analysis: Total response of a damped system