Related Experiment Video
Updated: Oct 9, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Kernel and nonlinear canonical correlation analysis
1Applied Computational Intelligence Research Unit, The University of Paisley, Scotland.
Abstract:
We review a neural implementation of the statistical technique of Canonical Correlation Analysis (CCA) and extend it to nonlinear CCA. We then derive the method of kernel-based CCA and compare these two methods on real and artificial data sets before using both on the Blind Separation of Sources.
Related Concept Videos
Calculating and Interpreting the Linear Correlation Coefficient
Coefficient of Correlation
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the strength of the linear...
Correlation and Regression
Calibration Curves: Correlation Coefficient
Calibration Curves: Linear Least Squares
For data that follow a straight line, the standard method for fitting is the linear...
Correlation of Experimental Data
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity, and...
