Howtosignalprocessing
How to do independent component analysis?
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other.
What is ICA in problem solving?
Independent Component Analysis (ICA) is a technique that allows the separation of a mixture of signals into their different sources, by assuming non Gaussian signal distribution (Yao et al., 2012).
How do you perform ICA?
To perform ICA, we can use fastICA R package. We have to install fastICA package in R or R studio. A data matrix with n rows representing observations and p columns representing variables. Number of components to be extracted.
