---
title: "FastICA in JavaScript and TypeScript"
description: "Separate statistically independent signals with the @kanaries/ml FastICA JavaScript implementation in browser and Node.js environments."
canonical_url: "https://ml.kanaries.net/docs/apis/decomposition/fastICA"
markdown_url: "https://ml.kanaries.net/docs/apis/decomposition/fastICA.md"
---
# FastICA in JavaScript

## Algorithm overview

FastICA recovers statistically independent sources from observed mixtures by maximizing non-Gaussianity. Common uses include blind source separation, artifact removal, and exploratory feature extraction.

## JavaScript implementation

`@kanaries/ml` offers parallel and deflation FastICA with deterministic initialization, whitening choices, transforms, and inverse transforms for JS-only signal and analytics workflows.

## Quick start example

```ts
import { Decomposition } from '@kanaries/ml';

const observedSignals = [[0, 1], [1, 0], [2, 1], [1, 2], [-1, 0]];
const ica = new Decomposition.FastICA({
  nComponents: 2,
  whiten: 'unit-variance',
  randomState: 0,
});
const sources = ica.fitTransform(observedSignals);
const reconstructed = ica.inverseTransform(sources);
console.log({ sources, reconstructed });
```

## Detailed API reference

Options include `nComponents`, `algorithm: 'parallel' | 'deflation'`, `whiten: 'unit-variance' | 'arbitrary-variance' | false`, `fun: 'logcosh' | 'exp' | 'cube'`, `funArgs.alpha`, `maxIter`, `tol`, and `randomState`.

Methods: `fit`, `transform`, `fitTransform`, `inverseTransform`. Learned fields: `components`, `mixing`, `mean`, and `nIter`. With `whiten: false`, input is not centered and `nComponents` is ignored, matching sklearn semantics.