Independent Component Analysis

The goal of blind source separation (BSS) is to recover independent sources given only sensor observations that are linear mixtures of independent source signals. The term blind indicates that both the source signals and the way the signals were mixed are unknown. Independent Component Analysis (ICA) is a method for solving the blind source separation problem. It is a way to find a linear coordinate system (the unmixing system) such that the resulting signals are as statistically independent from each other as possible. In contrast to correlation-based transformations such as Principal Component Analysis (PCA), ICA not only decorrelates the signals (2nd-order statistics) but also reduces higher-order statistical dependencies.