The Power of Independent Component Analysis (ICA) on Real-World Applications — EEG Example

<p>Independent component analysis (ICA) is usually associated with dimensionality reduction tasks. However, the technique&#39;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&nbsp;<em>&ldquo;Cocktail Party&rdquo;</em>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.</p> <p><a href="https://towardsdatascience.com/the-power-of-independent-component-analysis-ica-on-real-world-applications-egg-example-48df336a1bd8"><strong>Visit Now</strong></a></p>