# A Tutorial on Independent Component Analysis

arXiv: https://arxiv.org/abs/1404.2986 · HTML: https://mlsanity.com/paper/1404.2986/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2014.

## Built on by (most cited first, 2 of 2)

- [On the Use of Dimension Reduction or Signal Separation Methods for Nitrogen River Pollution Source Identification](https://mlsanity.com/paper/2204.13182/) (2022)
- [MAJL: A Model-Agnostic Joint Learning Framework for Music Source Separation and Pitch Estimation](https://mlsanity.com/paper/2501.03689/) (2025)

## Abstract (arXiv)

Independent component analysis (ICA) has become a standard data analysis technique applied to an array of problems in signal processing and machine learning. This tutorial provides an introduction to ICA based on linear algebra formulating an intuition for ICA from first principles. The goal of this tutorial is to provide a solid foundation on this advanced topic so that one might learn the motivation behind ICA, learn why and when to apply this technique and in the process gain an introduction to this exciting field of active research.