The correct answer is: A. ICA
ICA stands for Independent Component Analysis. It is a statistical method that can be used to find new variables that are linear combinations of the original set with independent components. ICA is often used in signal processing and machine learning applications.
PCA stands for Principal Component Analysis. It is a statistical method that can be used to find new variables that are linear combinations of the original set with the largest possible variance. PCA is often used in data visualization and dimensionality reduction applications.
SCA stands for Sparse Coding Analysis. It is a statistical method that can be used to find new variables that are linear combinations of the original set with the sparsest possible representation. SCA is often used in image denoising and compression applications.
In conclusion, ICA is the only method that can be used to find new variables that are linear combinations of the original set with independent components.