• Similar to PCA, ICA determines a linear coordinate system for the data, transforming it by matrix W into a new space
  
• The transformation is free to be non-orthogonal

• The axes are sensitive to statistics of all orders, while for PCA they are only sensitive to the second order statistics

• Besides being uncorrelated, the vectors are also independent in the new space