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Independent Component Analysis

Date: January 7 2021

Summary: What independent component analysis is

Keywords: ##zettel #mathematics #analysis #independent #component #analysis #speech #fmri #noise #separation #archive


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Table of Contents

  1. How To Cite
  2. References
  3. Discussion:

ICA seeks to minimize mutual information between projections.Independent component analysis finds a coordinate frame onto which the projection of the data has minimal temporal overlap. [1]

ICA is considered a linear decomposition alternative to principal component analysis (PCA). In PCA, the data is represented using perpendicular axes. ICA is not limited by this constraint [2]

ICA has been applied to domains such as:

ICA decompositions are best for sources linearly mixed in a recorded signal.

How To Cite

Zelko, Jacob. Independent Component Analysis. January 7 2021.


[1] A. Delorme, S. Makeig, M. Fabre-Thorpe, and T. Sejnowski, “From single-trial EEG to brain area dynamics,” Neurocomputing, vol. 44–46, pp. 1057–1064, Jun. 2002, doi: 10.1016/S0925-2312(02)00415-0.

[2] S. Makeig et al., “Functionally independent components of the late positive event-related potential during visual spatial attention,” J. Neurosci., vol. 19, no. 7, pp. 2665–2680, 1999.

[3] H.-M. Park, H.-Y. Jung, T.-W. Lee, and S.-Y. Lee, “Subband-based blind signal separation for noisy speech recognition,” Electron. Lett., vol. 35, no. 23, pp. 2011–2012, 1999.


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