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Lecture Notes in Computer Science
Linear Independent Component Analysis considers the problem of nding a linear transformation that makes the components of the output vector statistically independent. This can be applied to blind source separation, where the input data consist of unknown linear mixtures of unknown independent source signals. The original source signals can be recovered from their mixtures using the assumption that they are statistically independent. More generally we can consider nonlinear mappings that makedoi:10.1007/3-540-61510-5_137 fatcat:xwex7tsbf5akjnnrb6oz5oagoe