Skip to content

MATLAB script of Independent Component Analysis (ICA) based on natural gradient algorithm

Notifications You must be signed in to change notification settings

d-kitamura/naturalGradICA

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Independent Component Analysis Based on Natural Gradient Algorithm

About

Sample MATLAB script for independent component analysis (ICA) based on natural gradient algorithm and its application to blind audio source separation.

Contents

  • input [dir]: includes test audio signals (dry source signals)
  • main.m: main script with parameter settings
  • naturalGradIca.m: function of ICA based on natural gradient algorithm

Usage Note

ICA assumes instantaneous mixing system (mixing matrix applied to time-domain signal) and separate sources by estimating inverse matrix. This mixing assumption is invalid in an actual audio mixing case because room reverberation exists anywhere. In such a reverberant mixing situation, the mixing system becomes not the instantaneous mixture but convolutive mixture. Therefore, simple ICA cannot separate such reverberant audio mixtures. In this sample script, the source signals are mixed with instantaneous mixture matrix A, and ICA estimates its inverse matrix in a blind manner.

Original paper

ICA and its optimization algorithm (natural gradient) were proposed in the following papers, respectively:

  • P. Comon, "Independent component analysis, a new concept?," Signal processing, vol. 36, no. 3, pp. 287-314, 1994.
  • S. Amari, "Natural gradient works efficiently in learning," Neural Computation, vol. 10, no. 2, pp. 251-276, 1998.

See Also

About

MATLAB script of Independent Component Analysis (ICA) based on natural gradient algorithm

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages