Independent Component Analysis

Independent Component Analysis (ICA) is a statistical technique that separates a mixture of signals into their original sources by identifying components that are statistically independent. Imagine hearing multiple people talking simultaneously; ICA helps to isolate each individual’s voice from the combined audio. It works by analyzing the observed data and finding a transformation that makes these separated components as independent as possible, revealing the original signals hidden within a mixture. ICA is useful in fields like brain imaging, audio processing, and data analysis where identifying underlying sources is essential.