Independent component analysis (ICA) is usually associated with dimensionality reduction tasks. However, the technique's most prominent application is separating linear contributions from the data, finding statistically independent components. For example, ICA is widely used as a tool to separate instrument tracks from audio. The objective of this article is to introduce and motivate ICA with the famous “Cocktail Party”example, then, a brief introduction to how ICA extracts independent components, using the basics of probability and information theory. Then, we explore a practical example of eye blink motion identification and removal from electroencephalogram (EEG) data.
Analysis Nobody Asked For: NBA Blocks per Game
In the 2023–24 NBA Season, two rookies (Victor Wembenyama and Chet Holmgren) are in the top 5 of blocks per game, and are performing…